[Robast-commits] r25 - in pkg: . ROptEst ROptEst/R ROptEst/chm ROptEst/man ROptEst.Rcheck ROptEst.Rcheck/ROptEst ROptEst.Rcheck/ROptEst/Meta ROptEst.Rcheck/ROptEst/R ROptEst.Rcheck/ROptEst/R-ex ROptEst.Rcheck/ROptEst/chtml ROptEst.Rcheck/ROptEst/help ROptEst.Rcheck/ROptEst/html ROptEst.Rcheck/ROptEst/latex ROptEst.Rcheck/ROptEst/man ROptEst.Rcheck/ROptEst/scripts ROptEst.Rcheck/ROptEst/tests RobAStBase RobAStBase/R RobAStBase/chm RobAStBase/man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sat Feb 16 04:32:42 CET 2008
Author: ruckdeschel
Date: 2008-02-16 04:32:41 +0100 (Sat, 16 Feb 2008)
New Revision: 25
Added:
pkg/ROptEst.Rcheck/
pkg/ROptEst.Rcheck/00check.log
pkg/ROptEst.Rcheck/00install.out
pkg/ROptEst.Rcheck/R.css
pkg/ROptEst.Rcheck/ROptEst-Ex.R
pkg/ROptEst.Rcheck/ROptEst-Ex.Rout
pkg/ROptEst.Rcheck/ROptEst-Ex.ps
pkg/ROptEst.Rcheck/ROptEst/
pkg/ROptEst.Rcheck/ROptEst/CONTENTS
pkg/ROptEst.Rcheck/ROptEst/DESCRIPTION
pkg/ROptEst.Rcheck/ROptEst/INDEX
pkg/ROptEst.Rcheck/ROptEst/MD5
pkg/ROptEst.Rcheck/ROptEst/Meta/
pkg/ROptEst.Rcheck/ROptEst/Meta/Rd.rds
pkg/ROptEst.Rcheck/ROptEst/Meta/hsearch.rds
pkg/ROptEst.Rcheck/ROptEst/Meta/nsInfo.rds
pkg/ROptEst.Rcheck/ROptEst/Meta/package.rds
pkg/ROptEst.Rcheck/ROptEst/NAMESPACE
pkg/ROptEst.Rcheck/ROptEst/R-ex/
pkg/ROptEst.Rcheck/ROptEst/R-ex/getL1normL2deriv.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/getL2normL2deriv.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/leastFavorableRadius.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/lowerCaseRadius.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/optIC.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/optRisk.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/radiusMinimaxIC.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/trAsCov-class.R
pkg/ROptEst.Rcheck/ROptEst/R-ex/trFiCov-class.R
pkg/ROptEst.Rcheck/ROptEst/R/
pkg/ROptEst.Rcheck/ROptEst/R/ROptEst
pkg/ROptEst.Rcheck/ROptEst/R/ROptEst.rdb
pkg/ROptEst.Rcheck/ROptEst/R/ROptEst.rdx
pkg/ROptEst.Rcheck/ROptEst/chtml/
pkg/ROptEst.Rcheck/ROptEst/chtml/ROptEst.chm
pkg/ROptEst.Rcheck/ROptEst/help/
pkg/ROptEst.Rcheck/ROptEst/help/AnIndex
pkg/ROptEst.Rcheck/ROptEst/help/getAsRisk
pkg/ROptEst.Rcheck/ROptEst/help/getBiasIC
pkg/ROptEst.Rcheck/ROptEst/help/getFiRisk
pkg/ROptEst.Rcheck/ROptEst/help/getFixClip
pkg/ROptEst.Rcheck/ROptEst/help/getFixRobIC
pkg/ROptEst.Rcheck/ROptEst/help/getIneffDiff
pkg/ROptEst.Rcheck/ROptEst/help/getInfCent
pkg/ROptEst.Rcheck/ROptEst/help/getInfClip
pkg/ROptEst.Rcheck/ROptEst/help/getInfGamma
pkg/ROptEst.Rcheck/ROptEst/help/getInfRobIC
pkg/ROptEst.Rcheck/ROptEst/help/getInfStand
pkg/ROptEst.Rcheck/ROptEst/help/getL1normL2deriv
pkg/ROptEst.Rcheck/ROptEst/help/getL2normL2deriv
pkg/ROptEst.Rcheck/ROptEst/help/getRiskIC
pkg/ROptEst.Rcheck/ROptEst/help/leastFavorableRadius
pkg/ROptEst.Rcheck/ROptEst/help/locMEstimator
pkg/ROptEst.Rcheck/ROptEst/help/lowerCaseRadius
pkg/ROptEst.Rcheck/ROptEst/help/minmaxBias
pkg/ROptEst.Rcheck/ROptEst/help/optIC
pkg/ROptEst.Rcheck/ROptEst/help/optRisk
pkg/ROptEst.Rcheck/ROptEst/help/radiusMinimaxIC
pkg/ROptEst.Rcheck/ROptEst/help/trAsCov-class
pkg/ROptEst.Rcheck/ROptEst/help/trFiCov-class
pkg/ROptEst.Rcheck/ROptEst/html/
pkg/ROptEst.Rcheck/ROptEst/html/00Index.html
pkg/ROptEst.Rcheck/ROptEst/html/getAsRisk.html
pkg/ROptEst.Rcheck/ROptEst/html/getBiasIC.html
pkg/ROptEst.Rcheck/ROptEst/html/getFiRisk.html
pkg/ROptEst.Rcheck/ROptEst/html/getFixClip.html
pkg/ROptEst.Rcheck/ROptEst/html/getFixRobIC.html
pkg/ROptEst.Rcheck/ROptEst/html/getIneffDiff.html
pkg/ROptEst.Rcheck/ROptEst/html/getInfCent.html
pkg/ROptEst.Rcheck/ROptEst/html/getInfClip.html
pkg/ROptEst.Rcheck/ROptEst/html/getInfGamma.html
pkg/ROptEst.Rcheck/ROptEst/html/getInfRobIC.html
pkg/ROptEst.Rcheck/ROptEst/html/getInfStand.html
pkg/ROptEst.Rcheck/ROptEst/html/getL1normL2deriv.html
pkg/ROptEst.Rcheck/ROptEst/html/getL2normL2deriv.html
pkg/ROptEst.Rcheck/ROptEst/html/getRiskIC.html
pkg/ROptEst.Rcheck/ROptEst/html/leastFavorableRadius.html
pkg/ROptEst.Rcheck/ROptEst/html/locMEstimator.html
pkg/ROptEst.Rcheck/ROptEst/html/lowerCaseRadius.html
pkg/ROptEst.Rcheck/ROptEst/html/minmaxBias.html
pkg/ROptEst.Rcheck/ROptEst/html/optIC.html
pkg/ROptEst.Rcheck/ROptEst/html/optRisk.html
pkg/ROptEst.Rcheck/ROptEst/html/radiusMinimaxIC.html
pkg/ROptEst.Rcheck/ROptEst/html/trAsCov-class.html
pkg/ROptEst.Rcheck/ROptEst/html/trFiCov-class.html
pkg/ROptEst.Rcheck/ROptEst/latex/
pkg/ROptEst.Rcheck/ROptEst/latex/getAsRisk.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getBiasIC.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getFiRisk.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getFixClip.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getFixRobIC.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getIneffDiff.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getInfCent.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getInfClip.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getInfGamma.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getInfRobIC.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getInfStand.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getL1normL2deriv.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getL2normL2deriv.tex
pkg/ROptEst.Rcheck/ROptEst/latex/getRiskIC.tex
pkg/ROptEst.Rcheck/ROptEst/latex/leastFavorableRadius.tex
pkg/ROptEst.Rcheck/ROptEst/latex/locMEstimator.tex
pkg/ROptEst.Rcheck/ROptEst/latex/lowerCaseRadius.tex
pkg/ROptEst.Rcheck/ROptEst/latex/minmaxBias.tex
pkg/ROptEst.Rcheck/ROptEst/latex/optIC.tex
pkg/ROptEst.Rcheck/ROptEst/latex/optRisk.tex
pkg/ROptEst.Rcheck/ROptEst/latex/radiusMinimaxIC.tex
pkg/ROptEst.Rcheck/ROptEst/latex/trAsCov-class.tex
pkg/ROptEst.Rcheck/ROptEst/latex/trFiCov-class.tex
pkg/ROptEst.Rcheck/ROptEst/man/
pkg/ROptEst.Rcheck/ROptEst/man/ROptEst.Rd.gz
pkg/ROptEst.Rcheck/ROptEst/scripts/
pkg/ROptEst.Rcheck/ROptEst/scripts/BinomialModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/ExponentialScaleModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/GammaModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/GumbelLocationModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/LognormalAndNormalModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/NormalLocationScaleModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/NormalScaleModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/PoissonModel.R
pkg/ROptEst.Rcheck/ROptEst/scripts/UnderOverShootRisk.R
pkg/ROptEst.Rcheck/ROptEst/tests/
pkg/ROptEst.Rcheck/ROptEst/tests/tests.R
pkg/ROptEst/R/L1L2normL2deriv.R
pkg/ROptEst/chm/getBiasIC.html
pkg/ROptEst/chm/getL1normL2deriv.html
pkg/ROptEst/chm/getL2normL2deriv.html
pkg/ROptEst/chm/minmaxBias.html
pkg/ROptEst/man/getBiasIC.Rd
pkg/ROptEst/man/getL1normL2deriv.Rd
pkg/ROptEst/man/getL2normL2deriv.Rd
pkg/ROptEst/man/minmaxBias.Rd
pkg/RobAStBase/chm/
pkg/RobAStBase/chm/00Index.html
pkg/RobAStBase/chm/ContIC-class.html
pkg/RobAStBase/chm/ContIC.html
pkg/RobAStBase/chm/ContNeighborhood-class.html
pkg/RobAStBase/chm/ContNeighborhood.html
pkg/RobAStBase/chm/FixRobModel-class.html
pkg/RobAStBase/chm/FixRobModel.html
pkg/RobAStBase/chm/IC-class.html
pkg/RobAStBase/chm/IC.html
pkg/RobAStBase/chm/InfRobModel-class.html
pkg/RobAStBase/chm/InfRobModel.html
pkg/RobAStBase/chm/InfluenceCurve-class.html
pkg/RobAStBase/chm/InfluenceCurve.html
pkg/RobAStBase/chm/Neighborhood-class.html
pkg/RobAStBase/chm/Rchm.css
pkg/RobAStBase/chm/RobAStBase.chm
pkg/RobAStBase/chm/RobAStBase.hhp
pkg/RobAStBase/chm/RobAStBase.toc
pkg/RobAStBase/chm/RobModel-class.html
pkg/RobAStBase/chm/TotalVarIC-class.html
pkg/RobAStBase/chm/TotalVarIC.html
pkg/RobAStBase/chm/TotalVarNeighborhood-class.html
pkg/RobAStBase/chm/TotalVarNeighborhood.html
pkg/RobAStBase/chm/UncondNeighborhood-class.html
pkg/RobAStBase/chm/checkIC.html
pkg/RobAStBase/chm/evalIC.html
pkg/RobAStBase/chm/generateIC.html
pkg/RobAStBase/chm/infoPlot.html
pkg/RobAStBase/chm/locMEstimator.html
pkg/RobAStBase/chm/logo.jpg
pkg/RobAStBase/chm/oneStepEstimator.html
Removed:
pkg/ROptEst/chm/BiasType-class.html
pkg/ROptEst/chm/BinomFamily.html
pkg/ROptEst/chm/ContIC-class.html
pkg/ROptEst/chm/ContIC.html
pkg/ROptEst/chm/ContNeighborhood-class.html
pkg/ROptEst/chm/ContNeighborhood.html
pkg/ROptEst/chm/DistrSymmList-class.html
pkg/ROptEst/chm/DistrSymmList.html
pkg/ROptEst/chm/DistributionSymmetry-class.html
pkg/ROptEst/chm/EllipticalSymmetry-class.html
pkg/ROptEst/chm/EllipticalSymmetry.html
pkg/ROptEst/chm/EvenSymmetric-class.html
pkg/ROptEst/chm/EvenSymmetric.html
pkg/ROptEst/chm/ExpScaleFamily.html
pkg/ROptEst/chm/FixRobModel-class.html
pkg/ROptEst/chm/FixRobModel.html
pkg/ROptEst/chm/FunSymmList-class.html
pkg/ROptEst/chm/FunSymmList.html
pkg/ROptEst/chm/FunctionSymmetry-class.html
pkg/ROptEst/chm/GammaFamily.html
pkg/ROptEst/chm/GumbelLocationFamily.html
pkg/ROptEst/chm/IC-class.html
pkg/ROptEst/chm/IC.html
pkg/ROptEst/chm/InfRobModel-class.html
pkg/ROptEst/chm/InfRobModel.html
pkg/ROptEst/chm/InfluenceCurve-class.html
pkg/ROptEst/chm/InfluenceCurve.html
pkg/ROptEst/chm/L2ParamFamily-class.html
pkg/ROptEst/chm/L2ParamFamily.html
pkg/ROptEst/chm/LnormScaleFamily.html
pkg/ROptEst/chm/Neighborhood-class.html
pkg/ROptEst/chm/NoSymmetry-class.html
pkg/ROptEst/chm/NoSymmetry.html
pkg/ROptEst/chm/NonSymmetric-class.html
pkg/ROptEst/chm/NonSymmetric.html
pkg/ROptEst/chm/NormLocationFamily.html
pkg/ROptEst/chm/NormLocationScaleFamily.html
pkg/ROptEst/chm/NormScaleFamily.html
pkg/ROptEst/chm/OddSymmetric-class.html
pkg/ROptEst/chm/OddSymmetric.html
pkg/ROptEst/chm/OptionalNumeric-class.html
pkg/ROptEst/chm/ParamFamParameter-class.html
pkg/ROptEst/chm/ParamFamParameter.html
pkg/ROptEst/chm/ParamFamily-class.html
pkg/ROptEst/chm/ParamFamily.html
pkg/ROptEst/chm/PoisFamily.html
pkg/ROptEst/chm/PosDefSymmMatrix-class.html
pkg/ROptEst/chm/PosDefSymmMatrix.html
pkg/ROptEst/chm/ProbFamily-class.html
pkg/ROptEst/chm/RiskType-class.html
pkg/ROptEst/chm/RobModel-class.html
pkg/ROptEst/chm/SphericalSymmetry-class.html
pkg/ROptEst/chm/SphericalSymmetry.html
pkg/ROptEst/chm/Symmetry-class.html
pkg/ROptEst/chm/TotalVarIC-class.html
pkg/ROptEst/chm/TotalVarIC.html
pkg/ROptEst/chm/TotalVarNeighborhood-class.html
pkg/ROptEst/chm/TotalVarNeighborhood.html
pkg/ROptEst/chm/UncondNeighborhood-class.html
pkg/ROptEst/chm/asBias-class.html
pkg/ROptEst/chm/asBias.html
pkg/ROptEst/chm/asCov-class.html
pkg/ROptEst/chm/asCov.html
pkg/ROptEst/chm/asGRisk-class.html
pkg/ROptEst/chm/asHampel-class.html
pkg/ROptEst/chm/asHampel.html
pkg/ROptEst/chm/asMSE-class.html
pkg/ROptEst/chm/asMSE.html
pkg/ROptEst/chm/asRisk-class.html
pkg/ROptEst/chm/asUnOvShoot-class.html
pkg/ROptEst/chm/asUnOvShoot.html
pkg/ROptEst/chm/asymmetricBias.html
pkg/ROptEst/chm/asymmetricBiasType-class.html
pkg/ROptEst/chm/checkIC.html
pkg/ROptEst/chm/checkL2deriv.html
pkg/ROptEst/chm/evalIC.html
pkg/ROptEst/chm/fiBias-class.html
pkg/ROptEst/chm/fiBias.html
pkg/ROptEst/chm/fiCov-class.html
pkg/ROptEst/chm/fiCov.html
pkg/ROptEst/chm/fiHampel-class.html
pkg/ROptEst/chm/fiHampel.html
pkg/ROptEst/chm/fiMSE-class.html
pkg/ROptEst/chm/fiMSE.html
pkg/ROptEst/chm/fiRisk-class.html
pkg/ROptEst/chm/fiUnOvShoot-class.html
pkg/ROptEst/chm/fiUnOvShoot.html
pkg/ROptEst/chm/generateIC.html
pkg/ROptEst/chm/infoPlot.html
pkg/ROptEst/chm/ksEstimator.html
pkg/ROptEst/chm/negativeBias.html
pkg/ROptEst/chm/oneStepEstimator.html
pkg/ROptEst/chm/onesidedBiasType-class.html
pkg/ROptEst/chm/positiveBias.html
pkg/ROptEst/chm/symmetricBias.html
pkg/ROptEst/chm/symmetricBiasType-class.html
pkg/ROptEst/chm/trAsCov.html
pkg/ROptEst/chm/trFiCov.html
pkg/ROptEst/man/infoPlot.Rd
pkg/ROptEst/man/ksEstimator.Rd
pkg/ROptEst/man/oneStepEstimator.Rd
pkg/ROptEst/man/trAsCov-class.Rd
pkg/ROptEst/man/trAsCov.Rd
pkg/ROptEst/man/trFiCov-class.Rd
pkg/ROptEst/man/trFiCov.Rd
Modified:
pkg/ROptEst/DESCRIPTION
pkg/ROptEst/NAMESPACE
pkg/ROptEst/R/AllClass.R
pkg/ROptEst/R/AllGeneric.R
pkg/ROptEst/R/getAsRisk.R
pkg/ROptEst/R/getFiRisk.R
pkg/ROptEst/R/getFixRobIC_fiUnOvShoot.R
pkg/ROptEst/R/getIneffDiff.R
pkg/ROptEst/R/getInfCent.R
pkg/ROptEst/R/getInfClip.R
pkg/ROptEst/R/getInfGamma.R
pkg/ROptEst/R/getInfRobIC_asBias.R
pkg/ROptEst/R/getInfRobIC_asCov.R
pkg/ROptEst/R/getInfRobIC_asGRisk.R
pkg/ROptEst/R/getInfRobIC_asHampel.R
pkg/ROptEst/R/getInfRobIC_asUnOvShoot.R
pkg/ROptEst/R/getInfStand.R
pkg/ROptEst/R/getRiskIC.R
pkg/ROptEst/R/leastFavorableRadius.R
pkg/ROptEst/R/lowerCaseRadius.R
pkg/ROptEst/R/optIC.R
pkg/ROptEst/R/optRisk.R
pkg/ROptEst/R/radiusMinimaxIC.R
pkg/ROptEst/chm/00Index.html
pkg/ROptEst/chm/ROptEst.chm
pkg/ROptEst/chm/ROptEst.hhp
pkg/ROptEst/chm/ROptEst.toc
pkg/ROptEst/chm/getAsRisk.html
pkg/ROptEst/chm/getFiRisk.html
pkg/ROptEst/chm/getFixClip.html
pkg/ROptEst/chm/getFixRobIC.html
pkg/ROptEst/chm/getIneffDiff.html
pkg/ROptEst/chm/getInfCent.html
pkg/ROptEst/chm/getInfClip.html
pkg/ROptEst/chm/getInfGamma.html
pkg/ROptEst/chm/getInfRobIC.html
pkg/ROptEst/chm/getInfStand.html
pkg/ROptEst/chm/getRiskIC.html
pkg/ROptEst/chm/leastFavorableRadius.html
pkg/ROptEst/chm/locMEstimator.html
pkg/ROptEst/chm/lowerCaseRadius.html
pkg/ROptEst/chm/optIC.html
pkg/ROptEst/chm/optRisk.html
pkg/ROptEst/chm/radiusMinimaxIC.html
pkg/ROptEst/chm/trAsCov-class.html
pkg/ROptEst/chm/trFiCov-class.html
pkg/ROptEst/man/getAsRisk.Rd
pkg/ROptEst/man/getFiRisk.Rd
pkg/ROptEst/man/getFixClip.Rd
pkg/ROptEst/man/getFixRobIC.Rd
pkg/ROptEst/man/getIneffDiff.Rd
pkg/ROptEst/man/getInfCent.Rd
pkg/ROptEst/man/getInfClip.Rd
pkg/ROptEst/man/getInfGamma.Rd
pkg/ROptEst/man/getInfRobIC.Rd
pkg/ROptEst/man/getInfStand.Rd
pkg/ROptEst/man/getRiskIC.Rd
pkg/ROptEst/man/leastFavorableRadius.Rd
pkg/ROptEst/man/locMEstimator.Rd
pkg/ROptEst/man/lowerCaseRadius.Rd
pkg/ROptEst/man/optIC.Rd
pkg/ROptEst/man/optRisk.Rd
pkg/ROptEst/man/radiusMinimaxIC.Rd
pkg/RobAStBase/NAMESPACE
pkg/RobAStBase/R/FixRobModel.R
pkg/RobAStBase/man/ContIC-class.Rd
pkg/RobAStBase/man/ContIC.Rd
pkg/RobAStBase/man/FixRobModel-class.Rd
pkg/RobAStBase/man/FixRobModel.Rd
pkg/RobAStBase/man/IC-class.Rd
pkg/RobAStBase/man/IC.Rd
pkg/RobAStBase/man/InfRobModel-class.Rd
pkg/RobAStBase/man/InfluenceCurve-class.Rd
pkg/RobAStBase/man/Neighborhood-class.Rd
pkg/RobAStBase/man/RobModel-class.Rd
pkg/RobAStBase/man/TotalVarIC-class.Rd
pkg/RobAStBase/man/TotalVarIC.Rd
pkg/RobAStBase/man/checkIC.Rd
pkg/RobAStBase/man/infoPlot.Rd
Log:
-RobAStBase should now install
-onesided and asymmetric Biases are introduced;
-Susi Zitzmann's inequalities are implemented
to getInfRobIC_asGRisk.R
remains to be done:
-problem with example for leastFavorableRadius()
-onesided bias evaluation...
-some scripts may be obsolete...
-checks
Modified: pkg/ROptEst/DESCRIPTION
===================================================================
--- pkg/ROptEst/DESCRIPTION 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/DESCRIPTION 2008-02-16 03:32:41 UTC (rev 25)
@@ -3,7 +3,7 @@
Date: 2008-02-14
Title: Optimally robust estimation
Description: Optimally robust estimation using S4 classes and methods
-Depends: R(>= 2.4.0), methods, distr(>= 2.0), distrEx(>= 2.0), distrMod(>= 2.0), RandVar(>= 0.6.2)
+Depends: R(>= 2.4.0), methods, distr(>= 2.0), distrEx(>= 2.0), distrMod(>= 2.0), RandVar(>= 0.6.2), RobAStBase
Author: Matthias Kohl
Maintainer: Matthias Kohl <Matthias.Kohl at stamats.de>
SaveImage: no
Modified: pkg/ROptEst/NAMESPACE
===================================================================
--- pkg/ROptEst/NAMESPACE 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/NAMESPACE 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,6 +1,7 @@
import("distr")
import("distrEx")
import("distrMod")
+import("RobAStBase")
import("RandVar")
exportMethods("show",
@@ -49,4 +50,6 @@
"radiusMinimaxIC",
"getIneffDiff",
"leastFavorableRadius",
- "lowerCaseRadius")
+ "lowerCaseRadius",
+ "minmaxBias", "getBiasIC", "getL1normL2deriv")
+export("getL2normL2deriv")
\ No newline at end of file
Modified: pkg/ROptEst/R/AllClass.R
===================================================================
--- pkg/ROptEst/R/AllClass.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/AllClass.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -5,3 +5,5 @@
require("distrMod", character = TRUE, quietly = TRUE)
require("RandVar", character = TRUE, quietly = TRUE)
}
+
+
Modified: pkg/ROptEst/R/AllGeneric.R
===================================================================
--- pkg/ROptEst/R/AllGeneric.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/AllGeneric.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -11,7 +11,7 @@
}
if(!isGeneric("getAsRisk")){
setGeneric("getAsRisk",
- function(risk, L2deriv, neighbor, ...) standardGeneric("getAsRisk"))
+ function(risk, L2deriv, neighbor, biastype, ...) standardGeneric("getAsRisk"))
}
if(!isGeneric("getFiRisk")){
setGeneric("getFiRisk",
@@ -27,29 +27,29 @@
}
if(!isGeneric("getInfGamma")){
setGeneric("getInfGamma",
- function(L2deriv, risk, neighbor, ...) standardGeneric("getInfGamma"))
+ function(L2deriv, risk, neighbor, biastype, ...) standardGeneric("getInfGamma"))
}
if(!isGeneric("getInfCent")){
setGeneric("getInfCent",
- function(L2deriv, neighbor, ...) standardGeneric("getInfCent"))
+ function(L2deriv, neighbor, biastype, ...) standardGeneric("getInfCent"))
}
if(!isGeneric("getInfStand")){
setGeneric("getInfStand",
- function(L2deriv, neighbor, ...) standardGeneric("getInfStand"))
+ function(L2deriv, neighbor, biastype, ...) standardGeneric("getInfStand"))
}
if(!isGeneric("getRiskIC")){
setGeneric("getRiskIC",
- function(IC, risk, neighbor, L2Fam, ...) standardGeneric("getRiskIC"))
+ function(IC, risk, neighbor, L2Fam, ...) standardGeneric("getRiskIC"))
}
if(!isGeneric("optRisk")){
- setGeneric("optRisk", function(model, risk, ...) standardGeneric("optRisk"))
+ setGeneric("optRisk", function(model, risk, ...) standardGeneric("optRisk"))
}
if(!isGeneric("radiusMinimaxIC")){
setGeneric("radiusMinimaxIC", function(L2Fam, neighbor, risk, ...)
standardGeneric("radiusMinimaxIC"))
}
if(!isGeneric("getIneffDiff")){
- setGeneric("getIneffDiff", function(radius, L2Fam, neighbor, risk, ...)
+ setGeneric("getIneffDiff", function(radius, L2Fam, neighbor, risk, biastype, ...)
standardGeneric("getIneffDiff"))
}
if(!isGeneric("leastFavorableRadius")){
@@ -57,5 +57,17 @@
standardGeneric("leastFavorableRadius"))
}
if(!isGeneric("lowerCaseRadius")){
- setGeneric("lowerCaseRadius", function(L2Fam, neighbor, risk, ...) standardGeneric("lowerCaseRadius"))
+ setGeneric("lowerCaseRadius", function(L2Fam, neighbor, risk, biastype, ...) standardGeneric("lowerCaseRadius"))
}
+if(!isGeneric("minmaxBias")){
+ setGeneric("minmaxBias",
+ function(L2deriv, neighbor, biastype, ...) standardGeneric("minmaxBias"))
+}
+if(!isGeneric("getL1normL2deriv")){
+ setGeneric("getL1normL2deriv",
+ function(L2deriv, ...) standardGeneric("getL1normL2deriv"))
+}
+if(!isGeneric("getBiasIC")){
+ setGeneric("getBiasIC",
+ function(IC, neighbor, L2Fam, biastype, ...) standardGeneric("getBiasIC"))
+}
Added: pkg/ROptEst/R/L1L2normL2deriv.R
===================================================================
--- pkg/ROptEst/R/L1L2normL2deriv.R (rev 0)
+++ pkg/ROptEst/R/L1L2normL2deriv.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,20 @@
+getL2normL2deriv <-
+ function(aFinfo, cent, ...){sqrt(aFinfo+cent^2)}
+
+setMethod("getL1normL2deriv", signature(L2deriv = "UnivariateDistribution"),
+ function(L2deriv, cent, ...){
+ return(-2*m1df(L2deriv, cent) +cent*(2*p(L2deriv)(cent)-1))
+ })
+
+setMethod("getL1normL2deriv", signature(L2deriv = "RealRandVariable"),
+ function(L2deriv, cent, stand, Distr, ...){
+ integrandG <- function(x, L2, stand, cent){
+ X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
+ Y <- apply(X, 2, "%*%", t(stand))
+ res <- sqrt(colSums(Y^2))
+ return((res > 0)*res)
+ }
+
+ return(E(object = Distr, fun = integrandG, L2 = L2deriv,
+ stand = stand, cent = cent, useApply = FALSE))
+ })
Modified: pkg/ROptEst/R/getAsRisk.R
===================================================================
--- pkg/ROptEst/R/getAsRisk.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getAsRisk.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -3,8 +3,9 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asMSE",
L2deriv = "UnivariateDistribution",
- neighbor = "Neighborhood"),
- function(risk, L2deriv, neighbor, clip, cent, stand, trafo){
+ neighbor = "Neighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(),
+ clip = NULL, cent = NULL, stand, trafo){
if(!is.finite(neighbor at radius))
mse <- Inf
else
@@ -13,8 +14,9 @@
})
setMethod("getAsRisk", signature(risk = "asMSE",
L2deriv = "EuclRandVariable",
- neighbor = "Neighborhood"),
- function(risk, L2deriv, neighbor, clip, cent, stand, trafo){
+ neighbor = "Neighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(),
+ clip = NULL, cent = NULL, stand, trafo){
if(!is.finite(neighbor at radius))
mse <- Inf
else
@@ -27,9 +29,9 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood"),
- function(risk, L2deriv, neighbor, trafo){
- z <- q(L2deriv)(0.5)
+ neighbor = "ContNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), trafo){
+ z <- q(L2deriv)(0.5)
bias <- abs(as.vector(trafo))/E(L2deriv, function(x, z){abs(x - z)},
useApply = FALSE, z = z)
@@ -37,16 +39,17 @@
})
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "UnivariateDistribution",
- neighbor = "TotalVarNeighborhood"),
- function(risk, L2deriv, neighbor, trafo){
+ neighbor = "TotalVarNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), trafo){
bias <- abs(as.vector(trafo))/(-m1df(L2deriv, 0))
return(list(asBias = bias))
})
setMethod("getAsRisk", signature(risk = "asBias",
L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood"),
- function(risk, L2deriv, neighbor, Distr, L2derivDistrSymm, trafo,
+ neighbor = "ContNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), Distr,
+ L2derivDistrSymm, trafo,
z.start, A.start, maxiter, tol){
if(is.null(z.start)) z.start <- numeric(ncol(trafo))
if(is.null(A.start)) A.start <- trafo
@@ -89,8 +92,8 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asCov",
L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood"),
- function(risk, L2deriv, neighbor, clip, cent, stand){
+ neighbor = "ContNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
c0 <- clip/abs(as.vector(stand))
D1 <- L2deriv - cent/as.vector(stand)
Cov <- (clip^2*(p(D1)(-c0) + 1 - p(D1)(c0))
@@ -100,8 +103,8 @@
})
setMethod("getAsRisk", signature(risk = "asCov",
L2deriv = "UnivariateDistribution",
- neighbor = "TotalVarNeighborhood"),
- function(risk, L2deriv, neighbor, clip, cent, stand){
+ neighbor = "TotalVarNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
g0 <- cent/abs(as.vector(stand))
c0 <- clip/abs(as.vector(stand))
Cov <- (abs(as.vector(stand))^2*(g0^2*p(L2deriv)(g0)
@@ -112,8 +115,8 @@
})
setMethod("getAsRisk", signature(risk = "asCov",
L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood"),
- function(risk, L2deriv, neighbor, Distr, clip, cent, stand){
+ neighbor = "ContNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), Distr, clip, cent, stand){
Y <- as(stand %*% L2deriv - cent, "EuclRandVariable")
absY <- sqrt(Y %*% Y)
@@ -135,19 +138,20 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "trAsCov",
L2deriv = "UnivariateDistribution",
- neighbor = "UncondNeighborhood"),
- function(risk, L2deriv, neighbor, clip, cent, stand){
+ neighbor = "UncondNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand){
Cov <- getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
- clip = clip, cent = cent, stand = stand)$asCov
+ biastype = biastype, clip = clip, cent = cent, stand = stand)$asCov
return(list(trAsCov = as.vector(Cov)))
})
setMethod("getAsRisk", signature(risk = "trAsCov",
L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood"),
- function(risk, L2deriv, neighbor, Distr, clip, cent, stand){
+ neighbor = "ContNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), Distr, clip, cent, stand){
Cov <- getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
- Distr = Distr, clip = clip, cent = cent, stand = stand)$asCov
+ biastype = biastype, Distr = Distr, clip = clip,
+ cent = cent, stand = stand)$asCov
return(list(trAsCov = sum(diag(Cov))))
})
@@ -157,8 +161,8 @@
###############################################################################
setMethod("getAsRisk", signature(risk = "asUnOvShoot",
L2deriv = "UnivariateDistribution",
- neighbor = "UncondNeighborhood"),
- function(risk, L2deriv, neighbor, clip, cent, stand, trafo){
+ neighbor = "UncondNeighborhood", biastype = "BiasType"),
+ function(risk, L2deriv, neighbor, biastype = symmetricBias(), clip, cent, stand, trafo){
if(identical(all.equal(neighbor at radius, 0), TRUE))
return(list(asUnOvShoot = pnorm(-risk at width/sqrt(as.vector(stand)))))
@@ -170,3 +174,27 @@
return(list(asUnOvShoot = pnorm(-risk at width*s)))
})
+
+###############################################################################
+## asymptotic semivariance
+###############################################################################
+
+setMethod("getAsRisk", signature(risk = "asSemivar",
+ L2deriv = "UnivariateDistribution",
+ neighbor = "Neighborhood", biastype = "onesidedBias"),
+ function(risk, L2deriv, neighbor, biastype = positiveBias(),
+ clip, cent, stand, trafo){
+ A <- as.vector(stand)*as.vector(trafo)
+ r <- neighbor at radius
+ b <- clip*A
+ if (sign(biastype)>0)
+ v <- E(L2deriv, function(x) A^2*pmin(x-cent,clip)^2)
+ else
+ v <- E(L2deriv, function(x) A^2*pmax(x-cent,-clip)^2)
+ sv <- r*b/sqrt(v)
+ if(!is.finite(r))
+ semvar <- Inf
+ else
+ semvar <- (v+r^2*b^2)*pnorm(sv)+ r*b*sqrt(v)*dnorm(sv)
+ return(list(asSemivar = semvar))
+ })
Modified: pkg/ROptEst/R/getFiRisk.R
===================================================================
--- pkg/ROptEst/R/getFiRisk.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getFiRisk.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -41,8 +41,10 @@
setMethod("getFiRisk", signature(risk = "fiUnOvShoot",
Distr = "Norm",
- neighbor = "ContNeighborhood"),
- function(risk, Distr, neighbor, clip, stand, sampleSize, Algo, cont){
+ neighbor = "ContNeighborhood"
+ ),
+ function(risk, Distr, neighbor, clip, stand,
+ sampleSize, Algo, cont){
eps <- neighbor at radius
tau <- risk at width
n <- sampleSize
Modified: pkg/ROptEst/R/getFixRobIC_fiUnOvShoot.R
===================================================================
--- pkg/ROptEst/R/getFixRobIC_fiUnOvShoot.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getFixRobIC_fiUnOvShoot.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,7 +4,8 @@
setMethod("getFixRobIC", signature(Distr = "Norm",
risk = "fiUnOvShoot",
neighbor = "UncondNeighborhood"),
- function(Distr, risk, neighbor, sampleSize, upper, maxiter, tol, warn,
+ function(Distr, risk, neighbor,
+ sampleSize, upper, maxiter, tol, warn,
Algo, cont){
radius <- neighbor at radius
if(identical(all.equal(radius, 0), TRUE)){
Modified: pkg/ROptEst/R/getIneffDiff.R
===================================================================
--- pkg/ROptEst/R/getIneffDiff.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getIneffDiff.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,14 +4,15 @@
setMethod("getIneffDiff", signature(radius = "numeric",
L2Fam = "L2ParamFamily",
neighbor = "UncondNeighborhood",
- risk = "asMSE"),
- function(radius, L2Fam, neighbor, risk, loRad, upRad, loRisk, upRisk,
+ risk = "asMSE", biastype = "BiasType"),
+ function(radius, L2Fam, neighbor, risk, biastype = symmetricBias(),
+ loRad, upRad, loRisk, upRisk,
z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn){
L2derivDim <- numberOfMaps(L2Fam at L2deriv)
if(L2derivDim == 1){
neighbor at radius <- radius
res <- getInfRobIC(L2deriv = L2Fam at L2derivDistr[[1]], neighbor = neighbor,
- risk = risk, symm = L2Fam at L2derivDistrSymm[[1]],
+ risk = risk, biastype = biastype, symm = L2Fam at L2derivDistrSymm[[1]],
Finfo = L2Fam at FisherInfo, upper = upper.b,
trafo = L2Fam at param@trafo, maxiter = MaxIter, tol = eps, warn = warn)
trafo <- as.vector(L2Fam at param@trafo)
@@ -47,7 +48,7 @@
trafo <- L2Fam at param@trafo
neighbor at radius <- radius
res <- getInfRobIC(L2deriv = L2deriv, neighbor = neighbor, risk = risk,
- Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
+ biastype = biastype, Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
Finfo = L2Fam at FisherInfo, trafo = trafo, z.start = z.start,
A.start = A.start, upper = upper.b, maxiter = MaxIter,
Modified: pkg/ROptEst/R/getInfCent.R
===================================================================
--- pkg/ROptEst/R/getInfCent.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfCent.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -2,8 +2,10 @@
## centering constant for asymptotic MSE and asymptotic Hampel risk
###############################################################################
setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood"),
- function(L2deriv, neighbor, clip, cent, tol.z, symm, trafo){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(),
+ clip, cent, tol.z, symm, trafo){
if(symm) return(0)
z.fct <- function(z, c0, D1){
@@ -16,8 +18,10 @@
c0=clip, D1=L2deriv)$root)
})
setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
- neighbor = "TotalVarNeighborhood"),
- function(L2deriv, neighbor, clip, cent, tol.z, symm, trafo){
+ neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(),
+ clip, cent, tol.z, symm, trafo){
if(symm) return(-clip/2)
D1 <- sign(as.vector(trafo))*L2deriv
@@ -31,8 +35,10 @@
c0 = clip, D1 = D1)$root)
})
setMethod("getInfCent", signature(L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood"),
- function(L2deriv, neighbor, Distr, z.comp, stand, cent, clip){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(),
+ Distr, z.comp, stand, cent, clip){
integrand1 <- function(x, L2, clip, cent, stand){
X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
Y <- apply(X, 2, "%*%", t(stand))
@@ -63,3 +69,45 @@
return(res2/res1)
})
+###############################################################################
+## centering constant for asymptotic one-sided MSE and asymptotic one-sided Hampel risk
+###############################################################################
+setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"),
+ function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo){
+ if (sign(biastype)> 0){
+ z.fct <- function(z, c0, D1){
+ return(c0 - (z+c0)*p(D1)(z+c0) + m1df(D1, z+c0))
+ }
+ lower <- q(L2deriv)(getdistrOption("TruncQuantile"))
+ upper <- 0
+ }else{
+ z.fct <- function(z, c0, D1){
+ return(- z + (z-c0)*p(D1)(z-c0) - m1df(D1, z-c0))
+ }
+ lower <- 0
+ upper <- q(L2deriv)(1-getdistrOption("TruncQuantile"))
+ }
+ return(uniroot(z.fct, lower = lower, upper = upper, tol = tol.z,
+ c0=clip, D1=L2deriv)$root)
+ })
+
+setMethod("getInfCent", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"),
+ function(L2deriv, neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo){
+ nu1 <- nu(biastype)[1]
+ nu2 <- nu(biastype)[2]
+
+ z.fct <- function(z, c0, D1){
+ return(c0/nu2 + (z-c0/nu1)*p(D1)(z-c0/nu1) -
+ (z+c0/nu2)*p(D1)(z+c0/nu2) + m1df(D1, z+c0/nu2) -
+ m1df(D1, z-c0/nu1))
+ }
+ lower <- q(L2deriv)(getdistrOption("TruncQuantile"))
+ upper <- q(L2deriv)(1-getdistrOption("TruncQuantile"))
+
+ return(uniroot(z.fct, lower = lower, upper = upper, tol = tol.z,
+ c0=clip, D1=L2deriv)$root)
+ })
Modified: pkg/ROptEst/R/getInfClip.R
===================================================================
--- pkg/ROptEst/R/getInfClip.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfClip.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -5,34 +5,38 @@
L2deriv = "UnivariateDistribution",
risk = "asMSE",
neighbor = "ContNeighborhood"),
- function(clip, L2deriv, risk, neighbor, cent, symm, trafo){
+ function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ cent, symm, trafo){
return(neighbor at radius^2*clip +
getInfGamma(L2deriv = L2deriv, risk = risk,
- neighbor = neighbor, cent = cent, clip = clip))
+ neighbor = neighbor, biastype = biastype, cent = cent, clip = clip))
})
setMethod("getInfClip", signature(clip = "numeric",
L2deriv = "UnivariateDistribution",
risk = "asMSE",
neighbor = "TotalVarNeighborhood"),
- function(clip, L2deriv, risk, neighbor, cent, symm, trafo){
+ function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ cent, symm, trafo){
if(symm){
return(neighbor at radius^2*clip +
getInfGamma(L2deriv = sign(as.vector(trafo))*L2deriv, risk = risk,
- neighbor = neighbor, cent = -clip/2, clip = clip))
+ neighbor = neighbor, biastype = biastype, cent = -clip/2, clip = clip))
}else{
return(neighbor at radius^2*clip +
getInfGamma(L2deriv = sign(as.vector(trafo))*L2deriv, risk = risk,
- neighbor = neighbor, cent = cent, clip = clip))
+ neighbor = neighbor, biastype = biastype, cent = cent, clip = clip))
}
})
setMethod("getInfClip", signature(clip = "numeric",
L2deriv = "EuclRandVariable",
risk = "asMSE",
neighbor = "ContNeighborhood"),
- function(clip, L2deriv, risk, neighbor, Distr, stand, cent, trafo){
+ function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ Distr, stand, cent, trafo){
return(neighbor at radius^2*clip +
getInfGamma(L2deriv = L2deriv, risk = risk, neighbor = neighbor,
- Distr = Distr, stand = stand, cent = cent, clip = clip))
+ biastype = biastype, Distr = Distr, stand = stand,
+ cent = cent, clip = clip))
})
###############################################################################
@@ -42,14 +46,46 @@
L2deriv = "UnivariateDistribution",
risk = "asUnOvShoot",
neighbor = "UncondNeighborhood"),
- function(clip, L2deriv, risk, neighbor, cent, symm, trafo){
+ function(clip, L2deriv, risk, neighbor, biastype = symmetricBias(),
+ cent, symm, trafo){
if(symm){
return(neighbor at radius/risk at width +
getInfGamma(L2deriv = sign(as.vector(trafo))*L2deriv, risk = risk,
- neighbor = neighbor, cent = -clip/2, clip = clip))
+ neighbor = neighbor, biastype = biastype, cent = -clip/2, clip = clip))
}else{
return(neighbor at radius/risk at width +
getInfGamma(L2deriv = sign(as.vector(trafo))*L2deriv, risk = risk,
- neighbor = neighbor, cent = cent, clip = clip))
+ neighbor = neighbor, biastype = biastype, cent = cent, clip = clip))
}
})
+
+###############################################################################
+## optimal clipping bound for asymptotic semivariance
+###############################################################################
+setMethod("getInfClip", signature(clip = "numeric",
+ L2deriv = "UnivariateDistribution",
+ risk = "asSemivar",
+ neighbor = "ContNeighborhood"),
+ function(clip, L2deriv, risk, neighbor, cent, symm, trafo){
+ biastype <- if(sign(risk)==1) positiveBias() else negativeBias()
+ z0 <- getInfCent(L2deriv = L2deriv, risk = risk, neighbor = neighbor,
+ biastype = biastype,
+ clip = max(clip, 1e-4), cent = 0, trafo = trafo,
+ symm = symm, tol.z = 1e-6)
+
+ ga <- getInfGamma(L2deriv = L2deriv, risk = risk, neighbor = neighbor,
+ biastype = biastype, cent = cent, clip = clip)
+
+ r <- neighbor at radius
+
+ if (sign(risk)>0)
+ v0 <- E(L2deriv, function(x) pmin( x-z0, clip)^2 )
+ else
+ v0 <- E(L2deriv, function(x) pmax( x-z0, -clip)^2 )
+
+ s0 <- sqrt(v0)
+ sv <- r * clip / s0
+
+ er <- r^2 * clip + r * s0 * dnorm(sv) / pnorm(sv) + ga
+ return(er)
+ })
Modified: pkg/ROptEst/R/getInfGamma.R
===================================================================
--- pkg/ROptEst/R/getInfGamma.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfGamma.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -3,8 +3,9 @@
###############################################################################
setMethod("getInfGamma", signature(L2deriv = "UnivariateDistribution",
risk = "asMSE",
- neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, cent, clip){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), cent, clip){
c1 <- cent - clip
c2 <- cent + clip
return(m1df(L2deriv, c2) + m1df(L2deriv, c1)
@@ -16,14 +17,17 @@
###############################################################################
setMethod("getInfGamma", signature(L2deriv = "UnivariateDistribution",
risk = "asGRisk",
- neighbor = "TotalVarNeighborhood"),
- function(L2deriv, risk, neighbor, cent, clip){
+ neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), cent, clip){
return(m1df(L2deriv, cent+clip) + (cent+clip)*(1-p(L2deriv)(cent+clip)))
})
+
setMethod("getInfGamma", signature(L2deriv = "RealRandVariable",
risk = "asMSE",
- neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, Distr, stand, cent, clip){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip){
integrandG <- function(x, L2, stand, cent, clip){
X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
Y <- apply(X, 2, "%*%", t(stand))
@@ -41,7 +45,42 @@
###############################################################################
setMethod("getInfGamma", signature(L2deriv = "UnivariateDistribution",
risk = "asUnOvShoot",
- neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, cent, clip){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), cent, clip){
return(2*(m1df(L2deriv, cent+clip) + (cent+clip)*(1-p(L2deriv)(cent+clip))))
})
+
+###############################################################################
+## gamma in case of asymptotic one-sided convex asymptotic risk
+###############################################################################
+setMethod("getInfGamma", signature(L2deriv = "UnivariateDistribution",
+ risk = "asMSE",
+ neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"),
+ function(L2deriv, risk, neighbor, biastype = positiveBias(), cent, clip){
+ c1 <- cent - clip
+ c2 <- cent + clip
+ if (sign(biastype)<0)
+ return (m1df(L2deriv, c1) -c1*p(L2deriv)(c1))
+ else
+ return (m1df(L2deriv, c2) +c2*(1-p(L2deriv)(c2)))
+ })
+
+###############################################################################
+## gamma in case of a asymmetric asymptotic risk
+###############################################################################
+setMethod("getInfGamma", signature(L2deriv = "UnivariateDistribution",
+ risk = "asMSE",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"),
+ function(L2deriv, risk, neighbor, biastype = asymmetricBias(), cent, clip){
+ nu1 <- nu(biastype)[1]
+ nu2 <- nu(biastype)[2]
+
+ c1 <- cent - clip/nu1
+ c2 <- cent + clip/nu2
+ return(m1df(L2deriv, c2)/nu2 + m1df(L2deriv, c1)/nu1
+ - c1*p(L2deriv)(c1)/nu1 + c2*(1-p(L2deriv)(c2))/nu2)
+ })
+
Modified: pkg/ROptEst/R/getInfRobIC_asBias.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asBias.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfRobIC_asBias.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -3,9 +3,31 @@
###############################################################################
setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
risk = "asBias",
+ neighbor = "UncondNeighborhood"),
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), symm,
+ Finfo, trafo, upper, maxiter, tol, warn){
+
+ minmaxBias(L2deriv, neighbor, biastype, symm,
+ Finfo, trafo, upper, maxiter, tol, warn)
+ })
+setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
+ risk = "asBias",
neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, symm, Finfo, trafo,
- upper, maxiter, tol, warn){
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(),
+ Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, Finfo,
+ z.start, A.start, trafo, upper,
+ maxiter, tol, warn){
+ minmaxBias(L2deriv, neighbor, biastype,
+ Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, Finfo,
+ z.start, A.start, trafo, upper,
+ maxiter, tol, warn)
+ })
+
+setMethod("minmaxBias", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(), symm,
+ Finfo, trafo, upper, maxiter, tol, warn){
zi <- sign(as.vector(trafo))
A <- as.matrix(zi)
z <- q(L2deriv)(0.5)
@@ -26,10 +48,11 @@
return(list(A = A, a = zi*z, b = b, d = d, risk = Risk, info = info))
})
-setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
- risk = "asBias",
- neighbor = "TotalVarNeighborhood"),
- function(L2deriv, risk, neighbor, symm, Finfo, trafo,
+setMethod("minmaxBias", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(),
+ symm, Finfo, trafo,
upper, maxiter, tol, warn){
zi <- sign(as.vector(trafo))
A <- as.matrix(zi)
@@ -50,11 +73,12 @@
return(list(A = A, a = a, b = b, d = 1, risk = Risk, info = info))
})
-setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
- risk = "asBias",
- neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
- L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper,
+setMethod("minmaxBias", signature(L2deriv = "RealRandVariable",
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(),
+ Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, Finfo,
+ z.start, A.start, trafo, upper,
maxiter, tol, warn){
if(is.null(z.start)) z.start <- numeric(ncol(trafo))
if(is.null(A.start)) A.start <- trafo
@@ -103,3 +127,72 @@
return(list(A = A, a = a, b = b, d = d, risk = Risk, info = info))
})
+
+setMethod("minmaxBias", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"),
+ function(L2deriv, neighbor, biastype, symm,
+ Finfo, trafo, upper, maxiter, tol, warn){
+ nu1 <- nu(biastype)[1]
+ nu2 <- nu(biastype)[2]
+ zi <- sign(as.vector(trafo))
+ A <- as.matrix(zi)
+ z <- q(L2deriv)(nu1/(nu1+nu2))
+ b <- zi*as.vector(trafo)/E(L2deriv, function(x, z){(x - z)*(x>z)/nu2 +
+ (z-x)*(z>x)/nu1}, z = z)
+
+ b1 <- b / nu1
+ b2 <- b / nu2
+
+ p <- p(L2deriv)(z)
+
+ if(is(L2deriv, "AbscontDistribution"))
+ ws0 <- 0
+ else
+ ws0 <- d(L2deriv)(z)
+ if(ws0 > 0)
+ d <- (-b2*(1-p)+b1*(p-ws0))/ws0/b
+ else
+ d <- 0
+
+ info <- c("minimum asymptotic bias (lower case) solution")
+ asCov <- b2^2*(1-p)+b1^2*(p-ws0) + b^2*d^2*ws0
+ Risk <- list(asBias = b, asCov = asCov)
+
+ return(list(A = A, a = zi*z, b = b, d = d, risk = Risk, info = info))
+ })
+
+setMethod("minmaxBias", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"),
+ function(L2deriv, neighbor, biastype, symm,
+ Finfo, trafo, upper, maxiter, tol, warn){
+ nu1 <- nu(biastype)[1]
+ nu2 <- nu(biastype)[2]
+ zi <- sign(as.vector(trafo))
+ A <- as.matrix(zi)
+ z <- q(L2deriv)(nu1/(nu1+nu2))
+ b <- zi*as.vector(trafo)/E(L2deriv, function(x, z){(x - z)*(x>z)/nu2 +
+ (z-x)*(z>x)/nu1}, z = z)
+
+ b1 <- b / nu1
+ b2 <- b / nu2
+
+ p <- p(L2deriv)(z)
+
+ if(is(L2deriv, "AbscontDistribution"))
+ ws0 <- 0
+ else
+ ws0 <- d(L2deriv)(z)
+ if(ws0 > 0)
+ d <- (-b2*(1-p)+b1*(p-ws0))/ws0/b
+ else
+ d <- 0
+
+ info <- c("minimum asymptotic bias (lower case) solution")
+ asCov <- b2^2*(1-p)+b1^2*(p-ws0) + b^2*d^2*ws0
+ Risk <- list(asBias = b, asCov = asCov)
+
+ return(list(A = A, a = zi*z, b = b, d = d, risk = Risk, info = info))
+ })
+
\ No newline at end of file
Modified: pkg/ROptEst/R/getInfRobIC_asCov.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asCov.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfRobIC_asCov.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -15,7 +15,8 @@
setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
risk = "asCov",
neighbor = "TotalVarNeighborhood"),
- function(L2deriv, risk, neighbor, Finfo, trafo){
+ function(L2deriv, risk, neighbor,
+ Finfo, trafo){
info <- c("optimal IC in sense of Cramer-Rao bound")
A <- trafo %*% solve(Finfo)
b <- abs(as.vector(A))*(q(L2deriv)(1)-q(L2deriv)(0))
@@ -26,7 +27,8 @@
setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
risk = "asCov",
neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, Distr, Finfo, trafo){
+ function(L2deriv, risk, neighbor,
+ Distr, Finfo, trafo){
info <- c("optimal IC in sense of Cramer-Rao bound")
A <- trafo %*% solve(Finfo)
IC <- A %*% L2deriv
Modified: pkg/ROptEst/R/getInfRobIC_asGRisk.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asGRisk.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfRobIC_asGRisk.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,7 +4,7 @@
setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
risk = "asGRisk",
neighbor = "UncondNeighborhood"),
- function(L2deriv, risk, neighbor, symm, Finfo, trafo,
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
upper, maxiter, tol, warn){
radius <- neighbor at radius
if(identical(all.equal(radius, 0), TRUE)){
@@ -13,7 +13,8 @@
res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(),
neighbor = neighbor, Finfo = Finfo, trafo = trafo)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
+ biastype = biastype, clip = res$b, cent = res$a,
+ stand = res$A, trafo = trafo)
res$risk <- c(Risk, res$risk)
return(res)
}
@@ -29,25 +30,37 @@
iter <- iter + 1
z.old <- z
c0.old <- c0
- c0 <- try(uniroot(getInfClip, lower = .Machine$double.eps^0.75,
- upper = upper, tol = tol, L2deriv = L2deriv, risk = risk,
- neighbor = neighbor, cent = z, symm = S,
+
+upper = sqrt((Finfo+z^2)/((1+neighbor at radius^2)^2-1))
+
+ c0 <- try(uniroot(getInfClip,
+## new
+lower = getL1normL2deriv(L2deriv = L2deriv, cent = z)/ (1 + neighbor at radius^2),
+ #lower = .Machine$double.eps^0.75,
+upper = sqrt( ( Finfo + z^2 )/(( 1 + neighbor at radius^2)^2 - 1) ),
+ ## upper = upper,
+##
+ tol = tol, L2deriv = L2deriv, risk = risk,
+ neighbor = neighbor, biastype = biastype,
+ cent = z, symm = S,
trafo = trafo)$root, silent = TRUE)
if(!is.numeric(c0)){
if(warn) cat("The IC algorithm did not converge!\n",
"'radius >= maximum radius' for the given risk?\n",
"=> the minimum asymptotic bias (lower case) solution is returned\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asBias(),
- neighbor = neighbor, Finfo = Finfo,
+ neighbor = neighbor, biastype = biastype,
+ Finfo = Finfo,
symm = symm, trafo = trafo, upper = upper,
maxiter = maxiter, tol = tol, warn = warn)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
+ biastype = biastype,
+ clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
res$risk <- c(Risk, res$risk)
return(res)
}
- z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, clip = c0,
- cent = z, symm = S, trafo = trafo, tol.z = tol)
+ z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
+ clip = c0, cent = z, symm = S, trafo = trafo, tol.z = tol)
# cat("c0:\t", c0, "c0.old:\t", c0.old, "z:\t", z, "z.old:\t", z.old, "\n")
if(S) break
if(max(abs(z - z.old), abs(c0-c0.old)) < tol) break
@@ -58,11 +71,11 @@
}
info <- paste("optimally robust IC for", sQuote(class(risk)[1]))
A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor,
- clip = c0, cent = z, trafo = trafo)
+ biastype = biastype, clip = c0, cent = z, trafo = trafo)
a <- as.vector(A)*z
b <- abs(as.vector(A))*c0
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = b, cent = a, stand = A, trafo = trafo)
+ biastype = biastype, clip = b, cent = a, stand = A, trafo = trafo)
Risk <- c(Risk, list(asBias = b))
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info))
@@ -70,7 +83,8 @@
setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
risk = "asGRisk",
neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(),
+ Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, trafo, z.start, A.start, upper,
maxiter, tol, warn){
if(is.null(z.start)) z.start <- numeric(ncol(trafo))
@@ -83,7 +97,7 @@
res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(), neighbor = neighbor,
Distr = Distr, Finfo = Finfo, trafo = trafo)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
+ biastype = biastype, clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
res$risk <- c(Risk, res$risk)
return(res)
}
@@ -116,10 +130,18 @@
z.old <- z
b.old <- b
A.old <- A
- b <- try(uniroot(getInfClip, lower = .Machine$double.eps^0.75,
- upper = upper, tol = tol, L2deriv = L2deriv, risk = risk,
- Distr = Distr, neighbor = neighbor, stand = A, cent = z,
- trafo = trafo)$root, silent = TRUE)
+ b <- try(uniroot(getInfClip,
+
+## new
+lower = getL1normL2deriv(L2deriv = L2deriv, cent = z, stand = A,
+ Distr = Distr)/(1+neighbor at radius^2),
+upper = sqrt( sum( diag(A%*%Finfo%*%t(A)) + (A%*%z)^2) /
+ ((1 + neighbor at radius^2)^2-1)),
+##
+
+ tol = tol, L2deriv = L2deriv, risk = risk,
+ biastype = biastype, Distr = Distr, neighbor = neighbor,
+ stand = A, cent = z, trafo = trafo)$root, silent = TRUE)
if(!is.numeric(b)){
if(warn) cat("Could not determine optimal clipping bound!\n",
"'radius >= maximum radius' for the given risk?\n",
@@ -127,19 +149,22 @@
"If 'no' => Try again with modified starting values ",
"'z.start' and 'A.start'\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asBias(),
- neighbor = neighbor, Distr = Distr, DistrSymm = DistrSymm,
+ neighbor = neighbor, biastype = biastype,
+ Distr = Distr, DistrSymm = DistrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
z.start = z.start, A.start = A.start, trafo = trafo,
upper = upper, maxiter = maxiter, tol = tol, warn = warn)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
+ biastype = biastype, clip = res$b, cent = res$a,
+ stand = res$A, trafo = trafo)
res$risk <- c(Risk, res$risk)
return(res)
}
- z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, Distr = Distr,
- z.comp = z.comp, stand = A, cent = z, clip = b)
+ z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, z.comp = z.comp, stand = A, cent = z, clip = b)
A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor,
- Distr = Distr, A.comp = A.comp, stand = A, clip = b, cent = z,
+ biastype = biastype, Distr = Distr, A.comp = A.comp,
+ stand = A, clip = b, cent = z,
trafo = trafo)
prec <- max(abs(b-b.old), max(abs(A-A.old)), max(abs(z-z.old)))
cat("current precision in IC algo:\t", prec, "\n")
@@ -152,7 +177,8 @@
a <- as.vector(A %*% z)
info <- paste("optimally robust IC for", sQuote(class(risk)[1]))
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = b, cent = a, stand = A, trafo = trafo)
+ biastype = biastype,
+ clip = b, cent = a, stand = A, trafo = trafo)
Risk <- c(Risk, list(asBias = b))
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info))
Modified: pkg/ROptEst/R/getInfRobIC_asHampel.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asHampel.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfRobIC_asHampel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,7 +4,7 @@
setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
risk = "asHampel",
neighbor = "UncondNeighborhood"),
- function(L2deriv, risk, neighbor, symm, Finfo, trafo,
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
upper, maxiter, tol, warn){
A <- trafo / E(L2deriv, function(x){x^2})
b <- risk at bound
@@ -23,7 +23,8 @@
if(warn) cat("'b <= minimum asymptotic bias'\n",
"=> the minimum asymptotic bias (lower case) solution is returned\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asBias(),
- neighbor = neighbor, symm = symm,
+ neighbor = neighbor, biastype = biastype,
+ symm = symm,
trafo = trafo, maxiter = maxiter, tol = tol)
Risk <- list(asMSE = res$risk$asCov + neighbor at radius^2*bmin^2)
res$risk <- c(Risk, res$risk)
@@ -34,18 +35,21 @@
S <- symm at SymmCenter == 0
else
S <- FALSE
- z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor,
- clip = c0, cent = 0, trafo = trafo, tol.z = tol, symm = S)
+ z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype, clip = c0, cent = 0,
+ trafo = trafo, tol.z = tol, symm = S)
iter <- 0
repeat{
iter <- iter + 1
A.old <- A
z.old <- z
A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor,
- clip = c0, cent = z, trafo = trafo)
+ biastype = biastype,
+ clip = c0, cent = z, trafo = trafo)
c0 <- b/as.vector(A)
z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor,
- clip = c0, cent = z, trafo = trafo, tol.z = tol, symm = S)
+ biastype = biastype,
+ clip = c0, cent = z, trafo = trafo, tol.z = tol, symm = S)
if(max(abs(as.vector(A-A.old)), abs(z-z.old)) < tol) break
if(iter > maxiter){
cat("maximum iterations reached!\n", "achieved precision:\t",
@@ -56,7 +60,8 @@
info <- paste("optimally robust IC for 'asHampel' with bound =", round(b,3))
a <- as.vector(A)*z
Cov <- getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
- clip = b, cent = a, stand = A)$asCov
+ biastype = biastype,
+ clip = b, cent = a, stand = A)$asCov
Risk <- list(asCov = Cov, asBias = b, asMSE = Cov + neighbor at radius^2*b^2)
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info))
@@ -64,7 +69,7 @@
setMethod("getInfRobIC", signature(L2deriv = "RealRandVariable",
risk = "asHampel",
neighbor = "ContNeighborhood"),
- function(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, trafo, z.start, A.start, upper, maxiter, tol, warn){
if(is.null(z.start)) z.start <- numeric(ncol(trafo))
if(is.null(A.start)) A.start <- trafo
@@ -81,11 +86,12 @@
if(warn) cat("'b >= maximum asymptotic bias' => (classical) optimal IC\n",
"in sense of Cramer-Rao bound is returned\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(), neighbor = neighbor,
- Distr = Distr, Finfo = Finfo, trafo = trafo)
+ Distr = Distr, Finfo = Finfo, trafo = trafo)
return(res)
}
bmin <- getAsRisk(risk = asBias(), L2deriv = L2deriv, neighbor = neighbor,
- Distr = Distr, L2derivDistrSymm = L2derivDistrSymm,
+ biastype = biastype,
+ Distr = Distr, L2derivDistrSymm = L2derivDistrSymm,
trafo = trafo, z.start = z.start, A.start = A.start,
maxiter = maxiter, tol = tol)$asBias
cat("minimal bound:\t", bmin, "\n")
@@ -93,7 +99,8 @@
if(warn) cat("'b <= minimum asymptotic bias'\n",
"=> the minimum asymptotic bias (lower case) solution is returned\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asBias(), neighbor = neighbor,
- Distr = Distr, DistrSymm = DistrSymm, L2derivSymm = L2derivSymm,
+ biastype = biastype,
+ Distr = Distr, DistrSymm = DistrSymm, L2derivSymm = L2derivSymm,
L2derivDistrSymm = L2derivDistrSymm, z.start = z.start,
A.start = A.start, trafo = trafo, maxiter = maxiter,
tol = tol, warn = warn)
@@ -132,10 +139,11 @@
iter <- iter + 1
z.old <- z
A.old <- A
- z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, Distr = Distr,
- z.comp = z.comp, stand = A, cent = z, clip = b)
- A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor, clip = b, cent = z,
- A.comp = A.comp, trafo = trafo, Distr = Distr, stand = A)
+ z <- getInfCent(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
+ Distr = Distr, z.comp = z.comp, stand = A, cent = z, clip = b)
+ A <- getInfStand(L2deriv = L2deriv, neighbor = neighbor, biastype = biastype,
+ clip = b, cent = z, A.comp = A.comp, trafo = trafo,
+ Distr = Distr, stand = A)
prec <- max(max(abs(A-A.old)), max(abs(z-z.old)))
cat("current precision in IC algo:\t", prec, "\n")
if(prec < tol) break
@@ -147,7 +155,7 @@
info <- paste("optimally robust IC for 'asHampel' with bound =", round(b,3))
a <- as.vector(A %*% z)
Cov <- getAsRisk(risk = asCov(), L2deriv = L2deriv, neighbor = neighbor,
- Distr = Distr, clip = b, cent = a, stand = A)$asCov
+ biastype = biastype, Distr = Distr, clip = b, cent = a, stand = A)$asCov
Risk <- list(asCov = Cov, asBias = b, asMSE = sum(diag(Cov)) + neighbor at radius^2*b^2)
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info))
Modified: pkg/ROptEst/R/getInfRobIC_asUnOvShoot.R
===================================================================
--- pkg/ROptEst/R/getInfRobIC_asUnOvShoot.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfRobIC_asUnOvShoot.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,16 +4,17 @@
setMethod("getInfRobIC", signature(L2deriv = "UnivariateDistribution",
risk = "asUnOvShoot",
neighbor = "UncondNeighborhood"),
- function(L2deriv, risk, neighbor, symm, Finfo, trafo,
+ function(L2deriv, risk, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
upper, maxiter, tol, warn){
radius <- neighbor at radius
if(identical(all.equal(radius, 0), TRUE)){
if(warn) cat("'radius == 0' => (classical) optimal IC\n",
"in sense of Cramer-Rao bound is returned\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asCov(),
- neighbor = TotalVarNeighborhood(radius = neighbor at radius),
+ neighbor = TotalVarNeighborhood(radius = neighbor at radius),
Finfo = Finfo, trafo = trafo)
- Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
+ Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype,
clip = res$b, cent = res$a, stand = res$A, trafo = trafo)
res$risk <- c(Risk, res$risk)
return(res)
@@ -84,13 +85,14 @@
c0.old <- c0
c0 <- try(uniroot(getInfClip, lower = .Machine$double.eps^0.75,
upper = upper, tol = tol, L2deriv = L2deriv, risk = risk,
- neighbor = neighbor, cent = z, symm = S,
+ neighbor = neighbor, biastype = biastype,
+ cent = z, symm = S,
trafo = trafo)$root, silent = TRUE)
if(!is.numeric(c0)){
if(warn) cat("The IC algorithm did not converge!\n",
"=> the minimum asymptotic bias (lower case) solution is returned\n")
res <- getInfRobIC(L2deriv = L2deriv, risk = asBias(),
- neighbor = neighbor, Finfo = Finfo,
+ neighbor = neighbor, biastype = biastype, Finfo = Finfo,
symm = symm, trafo = trafo, upper = upper,
maxiter = maxiter, tol = tol, warn = warn)
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
@@ -99,7 +101,7 @@
return(res)
}
z <- getInfCent(L2deriv = L2deriv, neighbor = TotalVarNeighborhood(radius = neighbor at radius),
- clip = c0, cent = z, symm = S, trafo = trafo, tol.z = tol)
+ biastype = biastype, clip = c0, cent = z, symm = S, trafo = trafo, tol.z = tol)
# cat("c0:\t", c0, "c0.old:\t", c0.old, "z:\t", z, "z.old:\t", z.old, "\n")
if(S) break
if(max(abs(z - z.old), abs(c0-c0.old)) < tol) break
@@ -110,11 +112,11 @@
}
info <- paste("optimally robust IC for", sQuote(class(risk)[1]))
A <- getInfStand(L2deriv = L2deriv, neighbor = TotalVarNeighborhood(radius = neighbor at radius),
- clip = c0, cent = z, trafo = trafo)
+ biastype = biastype, clip = c0, cent = z, trafo = trafo)
a <- as.vector(A)*z
b <- abs(as.vector(A))*c0
Risk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = b, cent = a, stand = A, trafo = trafo)
+ biastype = biastype, clip = b, cent = a, stand = A, trafo = trafo)
return(list(A = A, a = a, b = b, d = NULL, risk = Risk, info = info))
})
Modified: pkg/ROptEst/R/getInfStand.R
===================================================================
--- pkg/ROptEst/R/getInfStand.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getInfStand.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -2,23 +2,27 @@
## standardizing matrix for asymptotic G-Risk
###############################################################################
setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
- neighbor = "ContNeighborhood"),
- function(L2deriv, neighbor, clip, cent, trafo){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(), clip, cent, trafo){
c1 <- cent - clip
c2 <- cent + clip
return(trafo/(m2df(L2deriv, c2) - m2df(L2deriv, c1)
+ c1*m1df(L2deriv, c1) - c2*m1df(L2deriv, c2)))
})
setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
- neighbor = "TotalVarNeighborhood"),
- function(L2deriv, neighbor, clip, cent, trafo){
+ neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(), clip, cent, trafo){
D1 <- sign(as.vector(trafo))*L2deriv
return(trafo/(m2df(D1, cent+clip) - m2df(D1, cent) + cent*m1df(D1, cent)
- (cent+clip)*m1df(D1, cent+clip)))
})
setMethod("getInfStand", signature(L2deriv = "RealRandVariable",
- neighbor = "ContNeighborhood"),
- function(L2deriv, neighbor, Distr, A.comp, stand, clip, cent, trafo){
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"),
+ function(L2deriv, neighbor, biastype = symmetricBias(),
+ Distr, A.comp, stand, clip, cent, trafo){
w.fct <- function(x, L2, stand, cent, clip){
X <- evalRandVar(L2, as.matrix(x))[,,1] - cent
Y <- apply(X, 2, "%*%", t(stand))
@@ -48,3 +52,33 @@
return(trafo %*% solve(erg))
})
+###############################################################################
+## standardizing constant for one-sided bias
+###############################################################################
+setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"),
+ function(L2deriv, neighbor, biastype = positiveBias(), clip, cent, trafo){
+ c1 <- if (sign(biastype)<0) cent - clip else -Inf
+ c2 <- if (sign(biastype)>0) cent + clip else Inf
+ m1 <- if (sign(biastype)<0) m2df(L2deriv, c1) else 0
+ m2 <- if (sign(biastype)>0) m2df(L2deriv, c2) else E(L2deriv, function(x)x^2)
+ c10 <- if (sign(biastype)<0) c1*m1df(L2deriv, c1) else 0
+ c20 <- if (sign(biastype)>0) c2*m1df(L2deriv, c2) else 0
+ return(trafo/(m2 - m1 + c10 - c20))
+ })
+
+###############################################################################
+## standardizing constant for asymmetric bias
+###############################################################################
+setMethod("getInfStand", signature(L2deriv = "UnivariateDistribution",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"),
+ function(L2deriv, neighbor, biastype = asymmetricBias(), clip, cent, trafo){
+ nu1 <- nu(biastype)[1]
+ nu2 <- nu(biastype)[2]
+ c1 <- cent - clip/nu1
+ c2 <- cent + clip/nu2
+ return(trafo/(m2df(L2deriv, c2) - m2df(L2deriv, c1)
+ + c1*m1df(L2deriv, c1) - c2*m1df(L2deriv, c2)))
+ })
Modified: pkg/ROptEst/R/getRiskIC.R
===================================================================
--- pkg/ROptEst/R/getRiskIC.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/getRiskIC.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -113,149 +113,19 @@
###############################################################################
setMethod("getRiskIC", signature(IC = "IC",
risk = "asBias",
- neighbor = "ContNeighborhood",
+ neighbor = "UncondNeighborhood",
L2Fam = "missing"),
- function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
- L2Fam <- eval(IC at CallL2Fam)
- D1 <- L2Fam at distribution
- trafo <- L2Fam at param@trafo
-
- IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
- absIC1 <- sqrt(IC1 %*% IC1)
- x <- as.matrix(r(D1)(1e5))
- x <- as.matrix(x[!duplicated(x),])
- Bias <- max(evalRandVar(absIC1, x))
-
- slots = slotNames(L2Fam at distribution@param)
- slots = slots[slots != "name"]
- nrvalues = length(slots)
- if (nrvalues > 0) {
- values = numeric(nrvalues)
- for (i in 1:nrvalues)
- values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
-
- paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
- }
- distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
-
- prec <- checkIC(IC, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
+ function(IC, risk, neighbor, biastype = symmetricBias(),
+ tol = .Machine$double.eps^0.25){
+ getBiasIC(IC, neighbor, biastype, tol)
})
setMethod("getRiskIC", signature(IC = "IC",
risk = "asBias",
- neighbor = "ContNeighborhood",
+ neighbor = "UncondNeighborhood",
L2Fam = "L2ParamFamily"),
- function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
- D1 <- L2Fam at distribution
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(D1)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
-
- trafo <- L2Fam at param@trafo
-
- IC1 <- as(diag(dimension(IC at Curve)) %*% IC at Curve, "EuclRandVariable")
- absIC1 <- sqrt(IC1 %*% IC1)
- x <- as.matrix(r(D1)(1e5))
- Bias <- max(evalRandVar(absIC1, x))
-
- slots = slotNames(L2Fam at distribution@param)
- slots = slots[slots != "name"]
- nrvalues = length(slots)
- if (nrvalues > 0) {
- values = numeric(nrvalues)
- for (i in 1:nrvalues)
- values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
-
- paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
- }
- distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
-
- prec <- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
+ function(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25){
+ getBiasIC(IC, neighbor, L2Fam, biastype, tol)
})
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "asBias",
- neighbor = "TotalVarNeighborhood",
- L2Fam = "missing"),
- function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
- L2Fam <- eval(IC at CallL2Fam)
- trafo <- L2Fam at param@trafo
- if(nrow(trafo) > 1)
- stop("not yet implemented for dimension > 1")
-
- D1 <- L2Fam at distribution
- IC1 <- as(diag(1) %*% IC at Curve, "EuclRandVariable")
- x <- as.matrix(r(D1)(1e5))
- res <- evalRandVar(IC1, x)
- Bias <- max(res) - min(res)
-
- slots = slotNames(L2Fam at distribution@param)
- slots = slots[slots != "name"]
- nrvalues = length(slots)
- if (nrvalues > 0) {
- values = numeric(nrvalues)
- for (i in 1:nrvalues)
- values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
-
- paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
- }
- distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
-
- prec <- checkIC(IC, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
- })
-setMethod("getRiskIC", signature(IC = "IC",
- risk = "asBias",
- neighbor = "TotalVarNeighborhood",
- L2Fam = "L2ParamFamily"),
- function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
- if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
- stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
-
- if(dimension(IC at Curve) > 1)
- stop("not yet implemented for dimension > 1")
-
- D1 <- L2Fam at distribution
- IC1 <- as(diag(1) %*% IC at Curve, "EuclRandVariable")
- x <- as.matrix(r(D1)(1e5))
- res <- evalRandVar(IC1, x)
- Bias <- max(res) - min(res)
-
- slots = slotNames(L2Fam at distribution@param)
- slots = slots[slots != "name"]
- nrvalues = length(slots)
- if (nrvalues > 0) {
- values = numeric(nrvalues)
- for (i in 1:nrvalues)
- values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
-
- paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
- }
- distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
-
- prec <- checkIC(IC, L2Fam, out = FALSE)
- if(prec > tol)
- warning("The maximum deviation from the exact IC properties is", prec,
- "\nThis is larger than the specified 'tol' ",
- "=> the result may be wrong")
-
- return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
- })
-
###############################################################################
## asymptotic MSE
###############################################################################
@@ -263,12 +133,12 @@
risk = "asMSE",
neighbor = "UncondNeighborhood",
L2Fam = "missing"),
- function(IC, risk, neighbor, tol = .Machine$double.eps^0.25){
+ function(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25){
rad <- neighbor at radius
if(rad == Inf) return(Inf)
trCov <- getRiskIC(IC = IC, risk = trAsCov())
- Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor)
+ Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor, biastype = biastype)
L2Fam <- eval(IC at CallL2Fam)
slots = slotNames(L2Fam at distribution@param)
@@ -297,7 +167,7 @@
risk = "asMSE",
neighbor = "UncondNeighborhood",
L2Fam = "L2ParamFamily"),
- function(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25){
+ function(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25){
if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
@@ -305,7 +175,7 @@
if(rad == Inf) return(Inf)
trCov <- getRiskIC(IC = IC, risk = trAsCov(), L2Fam = L2Fam)
- Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor, L2Fam = L2Fam)
+ Bias <- getRiskIC(IC = IC, risk = asBias(), neighbor = neighbor, L2Fam = L2Fam, biastype = biastype)
slots = slotNames(L2Fam at distribution@param)
slots = slots[slots != "name"]
@@ -637,3 +507,152 @@
return(list(fiUnOvShoot = list(distribution = distr, neighborhood = nghb, value = erg)))
})
+
+
+###############################################################################
+## asymptotic Bias for various types
+###############################################################################
+setMethod("getBiasIC", signature(IC = "IC",
+ neighbor = "ContNeighborhood",
+ L2Fam = "missing",
+ biastype = "BiasType"),
+ function(IC, neighbor, biastype, tol = .Machine$double.eps^0.25){
+ L2Fam <- eval(IC at CallL2Fam)
+ D1 <- L2Fam at distribution
+ trafo <- L2Fam at param@trafo
+
+ IC1 <- as(diag(nrow(trafo)) %*% IC at Curve, "EuclRandVariable")
+ absIC1 <- sqrt(IC1 %*% IC1)
+ x <- as.matrix(r(D1)(1e5))
+ x <- as.matrix(x[!duplicated(x),])
+ Bias <- max(evalRandVar(absIC1, x))
+
+ slots = slotNames(L2Fam at distribution@param)
+ slots = slots[slots != "name"]
+ nrvalues = length(slots)
+ if (nrvalues > 0) {
+ values = numeric(nrvalues)
+ for (i in 1:nrvalues)
+ values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
+
+ paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
+ }
+ distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
+
+ prec <- checkIC(IC, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
+ })
+setMethod("getBiasIC", signature(IC = "IC",
+ neighbor = "ContNeighborhood",
+ L2Fam = "L2ParamFamily",
+ biastype = "BiasType"),
+ function(IC, neighbor, L2Fam, biastype, tol = .Machine$double.eps^0.25){
+ D1 <- L2Fam at distribution
+ if(dimension(Domain(IC at Curve[[1]])) != dimension(img(D1)))
+ stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
+
+ trafo <- L2Fam at param@trafo
+
+ IC1 <- as(diag(dimension(IC at Curve)) %*% IC at Curve, "EuclRandVariable")
+ absIC1 <- sqrt(IC1 %*% IC1)
+ x <- as.matrix(r(D1)(1e5))
+ Bias <- max(evalRandVar(absIC1, x))
+
+ slots = slotNames(L2Fam at distribution@param)
+ slots = slots[slots != "name"]
+ nrvalues = length(slots)
+ if (nrvalues > 0) {
+ values = numeric(nrvalues)
+ for (i in 1:nrvalues)
+ values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
+
+ paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
+ }
+ distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
+
+ prec <- checkIC(IC, L2Fam, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
+ })
+setMethod("getBiasIC", signature(IC = "IC",
+ neighbor = "TotalVarNeighborhood",
+ L2Fam = "missing",
+ biastype = "BiasType"),
+ function(IC, neighbor, biastype, tol = .Machine$double.eps^0.25){
+ L2Fam <- eval(IC at CallL2Fam)
+ trafo <- L2Fam at param@trafo
+ if(nrow(trafo) > 1)
+ stop("not yet implemented for dimension > 1")
+
+ D1 <- L2Fam at distribution
+ IC1 <- as(diag(1) %*% IC at Curve, "EuclRandVariable")
+ x <- as.matrix(r(D1)(1e5))
+ res <- evalRandVar(IC1, x)
+ Bias <- max(res) - min(res)
+
+ slots = slotNames(L2Fam at distribution@param)
+ slots = slots[slots != "name"]
+ nrvalues = length(slots)
+ if (nrvalues > 0) {
+ values = numeric(nrvalues)
+ for (i in 1:nrvalues)
+ values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
+
+ paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
+ }
+ distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
+
+ prec <- checkIC(IC, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
+ })
+setMethod("getBiasIC", signature(IC = "IC",
+ neighbor = "TotalVarNeighborhood",
+ L2Fam = "L2ParamFamily",
+ biastype = "BiasType"),
+ function(IC, neighbor, L2Fam, biastype, tol = .Machine$double.eps^0.25){
+ if(dimension(Domain(IC at Curve[[1]])) != dimension(img(L2Fam at distribution)))
+ stop("dimension of 'Domain' of 'Curve' != dimension of 'img' of 'distribution' of 'L2Fam'")
+
+ if(dimension(IC at Curve) > 1)
+ stop("not yet implemented for dimension > 1")
+
+ D1 <- L2Fam at distribution
+ IC1 <- as(diag(1) %*% IC at Curve, "EuclRandVariable")
+ x <- as.matrix(r(D1)(1e5))
+ res <- evalRandVar(IC1, x)
+ Bias <- max(res) - min(res)
+
+ slots = slotNames(L2Fam at distribution@param)
+ slots = slots[slots != "name"]
+ nrvalues = length(slots)
+ if (nrvalues > 0) {
+ values = numeric(nrvalues)
+ for (i in 1:nrvalues)
+ values[i] = attributes(attributes(L2Fam at distribution)$param)[[slots[i]]]
+
+ paramstring = paste("(", paste(values, collapse = ", "), ")", sep = "")
+ }
+ distr <- paste(class(L2Fam at distribution)[1], paramstring, sep = "")
+
+ prec <- checkIC(IC, L2Fam, out = FALSE)
+ if(prec > tol)
+ warning("The maximum deviation from the exact IC properties is", prec,
+ "\nThis is larger than the specified 'tol' ",
+ "=> the result may be wrong")
+
+ return(list(asBias = list(distribution = distr, neighborhood = neighbor at type, value = Bias)))
+ })
Modified: pkg/ROptEst/R/leastFavorableRadius.R
===================================================================
--- pkg/ROptEst/R/leastFavorableRadius.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/leastFavorableRadius.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,8 +4,10 @@
###############################################################################
setMethod("leastFavorableRadius", signature(L2Fam = "L2ParamFamily",
neighbor = "UncondNeighborhood",
- risk = "asGRisk"),
- function(L2Fam, neighbor, risk, rho, upRad = 1, z.start = NULL,
+ risk = "asGRisk"# ,biastype = "BiasType"
+ ),
+ function(L2Fam, neighbor, risk, biastype = symmetricBias(),
+ rho, upRad = 1, z.start = NULL,
A.start = NULL, upper = 100, maxiter = 100,
tol = .Machine$double.eps^0.4, warn = FALSE){
if(length(rho) != 1)
@@ -15,7 +17,7 @@
L2derivDim <- numberOfMaps(L2Fam at L2deriv)
if(L2derivDim == 1){
- leastFavFct <- function(r, L2Fam, neighbor, risk, rho,
+ leastFavFct <- function(r, L2Fam, neighbor, risk, biastype, rho,
upper.b, MaxIter, eps, warn){
loRad <- r*rho
upRad <- r/rho
@@ -29,31 +31,34 @@
}else{
neighbor at radius <- loRad
resLo <- getInfRobIC(L2deriv = L2Fam at L2derivDistr[[1]], neighbor = neighbor,
- risk = risk, symm = L2Fam at L2derivDistrSymm[[1]],
+ risk = risk, biastype = biastype, symm = L2Fam at L2derivDistrSymm[[1]],
Finfo = L2Fam at FisherInfo, upper = upper.b,
trafo = L2Fam at param@trafo, maxiter = MaxIter, tol = eps, warn = warn)
loRisk <- getAsRisk(risk = risk, L2deriv = L2Fam at L2derivDistr[[1]],
- neighbor = neighbor, clip = resLo$b, cent = resLo$a,
+ neighbor = neighbor, biastype = biastype,
+ clip = resLo$b, cent = resLo$a,
stand = resLo$A, trafo = L2Fam at param@trafo)[[1]]
}
if(upRad == Inf){
bmin <- getAsRisk(risk = asBias(), L2deriv = L2Fam at L2derivDistr[[1]],
- neighbor = neighbor, trafo = L2Fam at param@trafo, symm = L2Fam at L2derivSymm[[1]])
+ neighbor = neighbor, biastype = biastype,
+ trafo = L2Fam at param@trafo, symm = L2Fam at L2derivSymm[[1]])
upRisk <- bmin^2
}else{
neighbor at radius <- upRad
resUp <- getInfRobIC(L2deriv = L2Fam at L2derivDistr[[1]], neighbor = neighbor,
- risk = risk, symm = L2Fam at L2derivDistrSymm[[1]],
+ risk = risk, biastype = biastype, symm = L2Fam at L2derivDistrSymm[[1]],
Finfo = L2Fam at FisherInfo, upper = upper.b,
trafo = L2Fam at param@trafo, maxiter = MaxIter, tol = eps, warn = warn)
upRisk <- getAsRisk(risk = risk, L2deriv = L2Fam at L2derivDistr[[1]],
- neighbor = neighbor, clip = resUp$b, cent = resUp$a,
+ neighbor = neighbor, biastype = biastype,
+ clip = resUp$b, cent = resUp$a,
stand = resUp$A, trafo = L2Fam at param@trafo)[[1]]
}
leastFavR <- uniroot(getIneffDiff, lower = lower, upper = upper,
tol = .Machine$double.eps^0.25, L2Fam = L2Fam, neighbor = neighbor,
- risk = risk, loRad = loRad, upRad = upRad, loRisk = loRisk,
+ risk = risk, biastype = biastype, loRad = loRad, upRad = upRad, loRisk = loRisk,
upRisk = upRisk, upper.b = upper.b, eps = eps, MaxIter = MaxIter,
warn = warn)$root
options(ow)
@@ -63,6 +68,7 @@
leastFavR <- optimize(leastFavFct, lower = 1e-4, upper = upRad,
tol = .Machine$double.eps^0.25, maximum = TRUE,
L2Fam = L2Fam, neighbor = neighbor, risk = risk,
+ biastype = biastype,
rho = rho, upper.b = upper, MaxIter = maxiter,
eps = tol, warn = warn)
@@ -91,7 +97,7 @@
L2derivDistrSymm <- new("DistrSymmList", L2)
}
}
- leastFavFct <- function(r, L2Fam, neighbor, risk, rho,
+ leastFavFct <- function(r, L2Fam, neighbor, risk, biastype, rho,
z.start, A.start, upper.b, MaxIter, eps, warn){
loRad <- r*rho
upRad <- r/rho
@@ -106,17 +112,20 @@
}else{
neighbor at radius <- loRad
resLo <- getInfRobIC(L2deriv = L2deriv, neighbor = neighbor, risk = risk,
- Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
+ biastype = biastype, Distr = L2Fam at distribution,
+ DistrSymm = L2Fam at distrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
Finfo = L2Fam at FisherInfo, trafo = trafo, z.start = z.start,
A.start = A.start, upper = upper.b, maxiter = MaxIter,
tol = eps, warn = warn)
loRisk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = resLo$b, cent = resLo$a, stand = resLo$A, trafo = trafo)[[1]]
+ biastype = biastype, clip = resLo$b, cent = resLo$a,
+ stand = resLo$A, trafo = trafo)[[1]]
}
if(upRad == Inf){
bmin <- getAsRisk(risk = asBias(), L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype,
Distr = L2Fam at distribution, L2derivDistrSymm = L2Fam at L2derivDistrSymm,
trafo = trafo, z.start = z.start, A.start = A.start,
maxiter = maxiter, tol = tol)$asBias
@@ -124,17 +133,20 @@
}else{
neighbor at radius <- upRad
resUp <- getInfRobIC(L2deriv = L2deriv, neighbor = neighbor, risk = risk,
+ biastype = biastype,
Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
Finfo = L2Fam at FisherInfo, trafo = trafo, z.start = z.start,
A.start = A.start, upper = upper.b, maxiter = maxiter,
tol = tol, warn = warn)
upRisk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
+ biastype = biastype,
clip = resUp$b, cent = resUp$a, stand = resUp$A, trafo = trafo)[[1]]
}
leastFavR <- uniroot(getIneffDiff, lower = lower, upper = upper,
tol = .Machine$double.eps^0.25, L2Fam = L2Fam, neighbor = neighbor,
- z.start = z.start, A.start = A.start, upper.b = upper.b, risk = risk,
+ biastype = biastype, z.start = z.start, A.start = A.start, upper.b = upper.b,
+ risk = risk,
loRad = loRad, upRad = upRad, loRisk = loRisk, upRisk = upRisk,
eps = eps, MaxIter = MaxIter, warn = warn)$root
options(ow)
@@ -146,6 +158,7 @@
leastFavR <- optimize(leastFavFct, lower = 1e-4, upper = upRad,
tol = .Machine$double.eps^0.25, maximum = TRUE,
L2Fam = L2Fam, neighbor = neighbor, risk = risk,
+ biastype = biastype,
rho = rho, z.start = z.start, A.start = A.start,
upper.b = upper, MaxIter = maxiter, eps = tol, warn = warn)
Modified: pkg/ROptEst/R/lowerCaseRadius.R
===================================================================
--- pkg/ROptEst/R/lowerCaseRadius.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/lowerCaseRadius.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -3,8 +3,9 @@
###############################################################################
setMethod("lowerCaseRadius", signature(L2Fam = "L2ParamFamily",
neighbor = "ContNeighborhood",
- risk = "asMSE"),
- function(L2Fam, neighbor, risk){
+ risk = "asMSE",
+ biastype = "BiasType"),
+ function(L2Fam, neighbor, risk, biastype = symmetricBias()){
if(length(L2Fam at param) != 1) stop("not yet implemented")
D1 <- L2Fam at distribution
@@ -52,8 +53,9 @@
})
setMethod("lowerCaseRadius", signature(L2Fam = "L2ParamFamily",
neighbor = "TotalVarNeighborhood",
- risk = "asMSE"),
- function(L2Fam, neighbor, risk){
+ risk = "asMSE",
+ biastype = "BiasType"),
+ function(L2Fam, neighbor, risk, biastype = symmetricBias()){
if(length(L2Fam at param) != 1) stop("not yet implemented")
D1 <- L2Fam at distribution
Modified: pkg/ROptEst/R/optIC.R
===================================================================
--- pkg/ROptEst/R/optIC.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/optIC.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -29,14 +29,14 @@
## Optimally robust IC for infinitesimal robust model and asymptotic risks
###############################################################################
setMethod("optIC", signature(model = "InfRobModel", risk = "asRisk"),
- function(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
+ function(model, risk, biastype = symmetricBias(), z.start = NULL, A.start = NULL, upper = 1e4,
maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE){
L2derivDim <- numberOfMaps(model at center@L2deriv)
if(L2derivDim == 1){
ow <- options("warn")
options(warn = -1)
res <- getInfRobIC(L2deriv = model at center@L2derivDistr[[1]],
- neighbor = model at neighbor, risk = risk,
+ neighbor = model at neighbor, risk = risk, biastype = biastype,
symm = model at center@L2derivDistrSymm[[1]],
Finfo = model at center@FisherInfo, trafo = model at center@param at trafo,
upper = upper, maxiter = maxiter, tol = tol, warn = warn)
@@ -67,7 +67,7 @@
ow <- options("warn")
options(warn = -1)
res <- getInfRobIC(L2deriv = L2deriv, neighbor = model at neighbor,
- risk = risk, Distr = model at center@distribution,
+ risk = risk, biastype = biastype, Distr = model at center@distribution,
DistrSymm = model at center@distrSymm, L2derivSymm = L2derivSymm,
L2derivDistrSymm = L2derivDistrSymm, Finfo = model at center@FisherInfo,
trafo = model at center@param at trafo, z.start = z.start, A.start = A.start,
@@ -86,13 +86,14 @@
## and asymptotic under-/overshoot risk
###############################################################################
setMethod("optIC", signature(model = "InfRobModel", risk = "asUnOvShoot"),
- function(model, risk, upper = 1e4, maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE){
+ function(model, risk, biastype = symmetricBias(), upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE){
L2derivDistr <- model at center@L2derivDistr[[1]]
if((length(model at center@L2derivDistr) == 1) & is(L2derivDistr, "UnivariateDistribution")){
ow <- options("warn")
options(warn = -1)
res <- getInfRobIC(L2deriv = L2derivDistr,
- neighbor = model at neighbor, risk = risk,
+ neighbor = model at neighbor, risk = risk, biastype = biastype,
symm = model at center@L2derivDistrSymm[[1]],
Finfo = model at center@FisherInfo, trafo = model at center@param at trafo,
upper = upper, maxiter = maxiter, tol = tol, warn = warn)
Modified: pkg/ROptEst/R/optRisk.R
===================================================================
--- pkg/ROptEst/R/optRisk.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/optRisk.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -10,14 +10,15 @@
## minimax asymptotic risk
###############################################################################
setMethod("optRisk", signature(model = "InfRobModel", risk = "asRisk"),
- function(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
+ function(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE){
L2derivDim <- numberOfMaps(model at center@L2deriv)
if(L2derivDim == 1){
ow <- options("warn")
options(warn = -1)
res <- getInfRobIC(L2deriv = model at center@L2derivDistr[[1]],
- neighbor = model at neighbor, risk = risk,
+ neighbor = model at neighbor, risk = risk, biastype = biastype,
symm = model at center@L2derivDistrSymm[[1]],
Finfo = model at center@FisherInfo, trafo = model at center@param at trafo,
upper = upper, maxiter = maxiter, tol = tol, warn = warn)
@@ -48,7 +49,7 @@
ow <- options("warn")
options(warn = -1)
res <- getInfRobIC(L2deriv = L2deriv, neighbor = model at neighbor,
- risk = risk, Distr = model at center@distribution,
+ risk = risk, biastype = biastype, Distr = model at center@distribution,
DistrSymm = model at center@distrSymm, L2derivSymm = L2derivSymm,
L2derivDistrSymm = L2derivDistrSymm, Finfo = model at center@FisherInfo,
trafo = model at center@param at trafo, z.start = z.start, A.start = A.start,
Modified: pkg/ROptEst/R/radiusMinimaxIC.R
===================================================================
--- pkg/ROptEst/R/radiusMinimaxIC.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/R/radiusMinimaxIC.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -5,7 +5,8 @@
setMethod("radiusMinimaxIC", signature(L2Fam = "L2ParamFamily",
neighbor = "UncondNeighborhood",
risk = "asGRisk"),
- function(L2Fam, neighbor, risk, loRad, upRad, z.start = NULL, A.start = NULL,
+ function(L2Fam, neighbor, risk, biastype = symmetricBias(),
+ loRad, upRad, z.start = NULL, A.start = NULL,
upper = 1e5, maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE){
if(length(loRad) != 1)
stop("'loRad' is not of length == 1")
@@ -27,7 +28,7 @@
}else{
neighbor at radius <- loRad
resLo <- getInfRobIC(L2deriv = L2Fam at L2derivDistr[[1]], neighbor = neighbor,
- risk = risk, symm = L2Fam at L2derivDistrSymm[[1]],
+ risk = risk, biastype = biastype, symm = L2Fam at L2derivDistrSymm[[1]],
Finfo = L2Fam at FisherInfo, upper = upper.b,
trafo = L2Fam at param@trafo, maxiter = maxiter, tol = tol, warn = warn)
loRisk <- getAsRisk(risk = risk, L2deriv = L2Fam at L2derivDistr[[1]],
@@ -37,12 +38,12 @@
if(upRad == Inf){
bmin <- getAsRisk(risk = asBias(), L2deriv = L2Fam at L2derivDistr[[1]],
- neighbor = neighbor, trafo = L2Fam at param@trafo)$asBias
+ neighbor = neighbor, biastype = biastype, trafo = L2Fam at param@trafo)$asBias
upRisk <- bmin^2
}else{
neighbor at radius <- upRad
resUp <- getInfRobIC(L2deriv = L2Fam at L2derivDistr[[1]], neighbor = neighbor,
- risk = risk, symm = L2Fam at L2derivDistrSymm[[1]],
+ risk = risk, biastype = biastype, symm = L2Fam at L2derivDistrSymm[[1]],
Finfo = L2Fam at FisherInfo, upper = upper.b,
trafo = L2Fam at param@trafo, maxiter = maxiter, tol = tol, warn = warn)
upRisk <- getAsRisk(risk = risk, L2deriv = L2Fam at L2derivDistr[[1]],
@@ -52,12 +53,13 @@
leastFavR <- uniroot(getIneffDiff, lower = lower, upper = upper,
tol = .Machine$double.eps^0.25, L2Fam = L2Fam, neighbor = neighbor,
+ biastype = biastype,
upper.b = upper.b, risk = risk, loRad = loRad, upRad = upRad,
loRisk = loRisk, upRisk = upRisk, eps = tol,
MaxIter = maxiter, warn = warn)$root
neighbor at radius <- leastFavR
res <- getInfRobIC(L2deriv = L2Fam at L2derivDistr[[1]], neighbor = neighbor,
- risk = risk, symm = L2Fam at L2derivSymm[[1]],
+ risk = risk, biastype = biastype, symm = L2Fam at L2derivSymm[[1]],
Finfo = L2Fam at FisherInfo, upper = upper.b,
trafo = L2Fam at param@trafo, maxiter = maxiter, tol = tol, warn = warn)
options(ow)
@@ -103,40 +105,41 @@
}else{
neighbor at radius <- loRad
resLo <- getInfRobIC(L2deriv = L2deriv, neighbor = neighbor, risk = risk,
- Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
+ biastype = biastype, Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
Finfo = L2Fam at FisherInfo, trafo = trafo, z.start = z.start,
A.start = A.start, upper = upper.b, maxiter = maxiter,
tol = tol, warn = warn)
loRisk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = resLo$b, cent = resLo$a, stand = resLo$A, trafo = trafo)[[1]]
+ biastype = biastype, clip = resLo$b, cent = resLo$a, stand = resLo$A, trafo = trafo)[[1]]
}
if(upRad == Inf){
bmin <- getAsRisk(risk = asBias(), L2deriv = L2deriv, neighbor = neighbor,
- Distr = L2Fam at distribution, L2derivDistrSymm = L2Fam at L2derivDistrSymm,
+ biastype = biastype, Distr = L2Fam at distribution, L2derivDistrSymm = L2Fam at L2derivDistrSymm,
trafo = trafo, z.start = z.start, A.start = A.start,
maxiter = maxiter, tol = tol)$asBias
upRisk <- bmin^2
}else{
neighbor at radius <- upRad
resUp <- getInfRobIC(L2deriv = L2deriv, neighbor = neighbor, risk = risk,
- Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
+ biastype = biastype, Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
Finfo = L2Fam at FisherInfo, trafo = trafo, z.start = z.start,
A.start = A.start, upper = upper.b, maxiter = maxiter,
tol = tol, warn = warn)
upRisk <- getAsRisk(risk = risk, L2deriv = L2deriv, neighbor = neighbor,
- clip = resUp$b, cent = resUp$a, stand = resUp$A, trafo = trafo)[[1]]
+ biastype = biastype, clip = resUp$b, cent = resUp$a, stand = resUp$A, trafo = trafo)[[1]]
}
leastFavR <- uniroot(getIneffDiff, lower = lower, upper = upper,
tol = .Machine$double.eps^0.25, L2Fam = L2Fam, neighbor = neighbor,
- z.start = z.start, A.start = A.start, upper.b = upper.b, risk = risk,
+ biastype = biastype, z.start = z.start, A.start = A.start, upper.b = upper.b, risk = risk,
loRad = loRad, upRad = upRad, loRisk = loRisk, upRisk = upRisk,
eps = tol, MaxIter = maxiter, warn = warn)$root
neighbor at radius <- leastFavR
res <- getInfRobIC(L2deriv = L2deriv, neighbor = neighbor, risk = risk,
+ biastype = biastype,
Distr = L2Fam at distribution, DistrSymm = L2Fam at distrSymm,
L2derivSymm = L2derivSymm, L2derivDistrSymm = L2derivDistrSymm,
Finfo = L2Fam at FisherInfo, trafo = trafo, z.start = z.start,
Modified: pkg/ROptEst/chm/00Index.html
===================================================================
--- pkg/ROptEst/chm/00Index.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/00Index.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -10,279 +10,62 @@
<param name="keyword" value=".. contents">
</object>
-<h2>Help pages for package ‘ROptEst’ version 0.5.0</h2>
+<h2>Help pages for package ‘ROptEst’ version 0.6.0</h2>
<p align="center">
-<a href="#A">A</a>
-<a href="#B">B</a>
-<a href="#C">C</a>
-<a href="#D">D</a>
-<a href="#E">E</a>
-<a href="#F">F</a>
<a href="#G">G</a>
-<a href="#I">I</a>
-<a href="#K">K</a>
<a href="#L">L</a>
<a href="#M">M</a>
-<a href="#N">N</a>
<a href="#O">O</a>
-<a href="#P">P</a>
<a href="#R">R</a>
-<a href="#S">S</a>
<a href="#T">T</a>
-<a href="#U">U</a>
-<a href="#W">W</a>
</p>
<table width="100%">
</table>
-<h2><a name="A">-- A --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="InfluenceCurve-class.html">addInfo<-,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">addProp<-,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">addRisk<-,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="asBias.html">asBias</a></td>
-<td>Generating function for asBias-class</td></tr>
-<tr><td width="25%"><a href="asBias-class.html">asBias-class</a></td>
-<td>Standardized Asymptotic Bias</td></tr>
-<tr><td width="25%"><a href="asCov.html">asCov</a></td>
-<td>Generating function for asCov-class</td></tr>
-<tr><td width="25%"><a href="asCov-class.html">asCov-class</a></td>
-<td>Asymptotic covariance</td></tr>
-<tr><td width="25%"><a href="asGRisk-class.html">asGRisk-class</a></td>
-<td>Convex asymptotic risk</td></tr>
-<tr><td width="25%"><a href="asHampel.html">asHampel</a></td>
-<td>Generating function for asHampel-class</td></tr>
-<tr><td width="25%"><a href="asHampel-class.html">asHampel-class</a></td>
-<td>Asymptotic Hampel risk</td></tr>
-<tr><td width="25%"><a href="asMSE.html">asMSE</a></td>
-<td>Generating function for asMSE-class</td></tr>
-<tr><td width="25%"><a href="asMSE-class.html">asMSE-class</a></td>
-<td>Asymptotic mean square error</td></tr>
-<tr><td width="25%"><a href="asRisk-class.html">asRisk-class</a></td>
-<td>Aymptotic risk</td></tr>
-<tr><td width="25%"><a href="asUnOvShoot.html">asUnOvShoot</a></td>
-<td>Generating function for asUnOvShoot-class</td></tr>
-<tr><td width="25%"><a href="asUnOvShoot-class.html">asUnOvShoot-class</a></td>
-<td>Asymptotic under-/overshoot probability</td></tr>
-<tr><td width="25%"><a href="asymmetricBias.html">asymmetricBias</a></td>
-<td>Generating function for asymmetricBiasType-class</td></tr>
-<tr><td width="25%"><a href="asymmetricBiasType-class.html">asymmetricBiasType-class</a></td>
-<td>asymmetric Bias Type</td></tr>
-</table>
-
-<h2><a name="B">-- B --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="BiasType-class.html">BiasType-class</a></td>
-<td>Bias Type</td></tr>
-<tr><td width="25%"><a href="BinomFamily.html">BinomFamily</a></td>
-<td>Generating function for Binomial families</td></tr>
-<tr><td width="25%"><a href="asHampel-class.html">bound</a></td>
-<td>Asymptotic Hampel risk</td></tr>
-<tr><td width="25%"><a href="asHampel-class.html">bound,asHampel-method</a></td>
-<td>Asymptotic Hampel risk</td></tr>
-<tr><td width="25%"><a href="fiHampel-class.html">bound,fiHampel-method</a></td>
-<td>Finite-sample Hampel risk</td></tr>
-</table>
-
-<h2><a name="C">-- C --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="IC-class.html">CallL2Fam</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="IC-class.html">CallL2Fam,IC-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">CallL2Fam<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="IC-class.html">CallL2Fam<-,IC-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">CallL2Fam<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">cent</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">cent,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">cent<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">center</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">center,RobModel-method</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">center<-,RobModel-method</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="checkIC.html">checkIC</a></td>
-<td>Generic Function for Checking ICs</td></tr>
-<tr><td width="25%"><a href="IC-class.html">checkIC,IC,L2ParamFamily-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="IC-class.html">checkIC,IC,missing-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="checkL2deriv.html">checkL2deriv</a></td>
-<td>Generic function for checking L2-derivatives</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">checkL2deriv,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">clip</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">clip,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">clip<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">clipLo</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">clipLo,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">clipLo<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">clipUp</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">clipUp,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">clipUp<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC.html">ContIC</a></td>
-<td>Generating function for ContIC-class</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">ContIC-class</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContNeighborhood.html">ContNeighborhood</a></td>
-<td>Generating function for ContNeighborhood-class</td></tr>
-<tr><td width="25%"><a href="ContNeighborhood-class.html">ContNeighborhood-class</a></td>
-<td>Contamination Neighborhood</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Curve</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Curve,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-</table>
-
-<h2><a name="D">-- D --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="ProbFamily-class.html">distribution</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">distribution,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></td>
-<td>Class of Symmetries for Distributions</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">distrSymm</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">distrSymm,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="DistrSymmList.html">DistrSymmList</a></td>
-<td>Generating function for DistrSymmList-class</td></tr>
-<tr><td width="25%"><a href="DistrSymmList-class.html">DistrSymmList-class</a></td>
-<td>List of Symmetries for a List of Distributions</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Domain,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-</table>
-
-<h2><a name="E">-- E --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="L2ParamFamily-class.html">E,L2ParamFamily,EuclRandMatrix,missing-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">E,L2ParamFamily,EuclRandVariable,missing-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">E,L2ParamFamily,EuclRandVarList,missing-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="EllipticalSymmetry.html">EllipticalSymmetry</a></td>
-<td>Generating function for EllipticalSymmetry-class</td></tr>
-<tr><td width="25%"><a href="EllipticalSymmetry-class.html">EllipticalSymmetry-class</a></td>
-<td>Class for Elliptically Symmetric Distributions</td></tr>
-<tr><td width="25%"><a href="evalIC.html">evalIC</a></td>
-<td>Generic function for evaluating ICs</td></tr>
-<tr><td width="25%"><a href="IC-class.html">evalIC,IC,matrix-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="IC-class.html">evalIC,IC,numeric-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="EvenSymmetric.html">EvenSymmetric</a></td>
-<td>Generating function for EvenSymmetric-class</td></tr>
-<tr><td width="25%"><a href="EvenSymmetric-class.html">EvenSymmetric-class</a></td>
-<td>Class for Even Functions</td></tr>
-<tr><td width="25%"><a href="ExpScaleFamily.html">ExpScaleFamily</a></td>
-<td>Generating function for exponential scale families</td></tr>
-</table>
-
-<h2><a name="F">-- F --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="fiBias.html">fiBias</a></td>
-<td>Generating function for fiBias-class</td></tr>
-<tr><td width="25%"><a href="fiBias-class.html">fiBias-class</a></td>
-<td>Finite-sample Bias</td></tr>
-<tr><td width="25%"><a href="fiCov.html">fiCov</a></td>
-<td>Generating function for fiCov-class</td></tr>
-<tr><td width="25%"><a href="fiCov-class.html">fiCov-class</a></td>
-<td>Finite-sample covariance</td></tr>
-<tr><td width="25%"><a href="fiHampel.html">fiHampel</a></td>
-<td>Generating function for fiHampel-class</td></tr>
-<tr><td width="25%"><a href="fiHampel-class.html">fiHampel-class</a></td>
-<td>Finite-sample Hampel risk</td></tr>
-<tr><td width="25%"><a href="fiMSE.html">fiMSE</a></td>
-<td>Generating function for fiMSE-class</td></tr>
-<tr><td width="25%"><a href="fiMSE-class.html">fiMSE-class</a></td>
-<td>Finite-sample mean square error</td></tr>
-<tr><td width="25%"><a href="fiRisk-class.html">fiRisk-class</a></td>
-<td>Finite-sample risk</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">FisherInfo</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">FisherInfo,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="fiUnOvShoot.html">fiUnOvShoot</a></td>
-<td>Generating function for fiUnOvShoot-class</td></tr>
-<tr><td width="25%"><a href="fiUnOvShoot-class.html">fiUnOvShoot-class</a></td>
-<td>Finite-sample under-/overshoot probability</td></tr>
-<tr><td width="25%"><a href="FixRobModel.html">FixRobModel</a></td>
-<td>Generating function for FixRobModel-class</td></tr>
-<tr><td width="25%"><a href="FixRobModel-class.html">FixRobModel-class</a></td>
-<td>Robust model with fixed (unconditional) neighborhood</td></tr>
-<tr><td width="25%"><a href="FunctionSymmetry-class.html">FunctionSymmetry-class</a></td>
-<td>Class of Symmetries for Functions</td></tr>
-<tr><td width="25%"><a href="FunSymmList.html">FunSymmList</a></td>
-<td>Generating function for FunSymmList-class</td></tr>
-<tr><td width="25%"><a href="FunSymmList-class.html">FunSymmList-class</a></td>
-<td>List of Symmetries for a List of Functions</td></tr>
-</table>
-
<h2><a name="G">-- G --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="GammaFamily.html">GammaFamily</a></td>
-<td>Generating function for Gamma families</td></tr>
-<tr><td width="25%"><a href="generateIC.html">generateIC</a></td>
-<td>Generic function for the generation of influence curves</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">generateIC,ContNeighborhood,L2ParamFamily-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">generateIC,TotalVarNeighborhood,L2ParamFamily-method</a></td>
-<td>Influence curve of total variation type</td></tr>
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,RealRandVariable,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,RealRandVariable,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,EuclRandVariable,Neighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,UnivariateDistribution,Neighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,RealRandVariable,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
-<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
<tr><td width="25%"><a href="getAsRisk.html">getAsRisk-methods</a></td>
<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,ContNeighborhood,missing,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC-methods</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
<tr><td width="25%"><a href="getFiRisk.html">getFiRisk</a></td>
<td>Generic Function for Computation of Finite-Sample Risks</td></tr>
<tr><td width="25%"><a href="getFiRisk.html">getFiRisk,fiUnOvShoot,Norm,ContNeighborhood-method</a></td>
@@ -307,18 +90,22 @@
<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff</a></td>
<td>Generic Function for the Computation of Inefficiency Differences</td></tr>
-<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE-method</a></td>
+<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method</a></td>
<td>Generic Function for the Computation of Inefficiency Differences</td></tr>
<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff-methods</a></td>
<td>Generic Function for the Computation of Inefficiency Differences</td></tr>
<tr><td width="25%"><a href="getInfCent.html">getInfCent</a></td>
<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfCent.html">getInfCent,RealRandVariable,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,TotalVarNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfCent.html">getInfCent-methods</a></td>
<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfClip.html">getInfClip</a></td>
@@ -329,20 +116,26 @@
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfClip.html">getInfClip-methods</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfGamma.html">getInfGamma</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,RealRandVariable,asMSE,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
-<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfGamma.html">getInfGamma-methods</a></td>
<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC</a></td>
@@ -355,10 +148,8 @@
<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method</a></td>
<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
-<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asBias,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method</a></td>
<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
-<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asBias,TotalVarNeighborhood-method</a></td>
-<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method</a></td>
<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method</a></td>
@@ -373,24 +164,34 @@
<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
<tr><td width="25%"><a href="getInfStand.html">getInfStand</a></td>
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
-<tr><td width="25%"><a href="getInfStand.html">getInfStand,RealRandVariable,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
-<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
-<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,TotalVarNeighborhood-method</a></td>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
<tr><td width="25%"><a href="getInfStand.html">getInfStand-methods</a></td>
<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv,RealRandVariable-method</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv,UnivariateDistribution-method</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv-methods</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL2normL2deriv.html">getL2normL2deriv</a></td>
+<td>Calculation of L2 norm of L2derivative</td></tr>
<tr><td width="25%"><a href="getRiskIC.html">getRiskIC</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,ContNeighborhood,L2ParamFamily-method</a></td>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,ContNeighborhood,missing-method</a></td>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,missing-method</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,TotalVarNeighborhood,L2ParamFamily-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,TotalVarNeighborhood,missing-method</a></td>
-<td>Generic function for the computation of a risk for an IC</td></tr>
<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,L2ParamFamily-method</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,missing-method</a></td>
@@ -411,114 +212,28 @@
<td>Generic function for the computation of a risk for an IC</td></tr>
<tr><td width="25%"><a href="getRiskIC.html">getRiskIC-methods</a></td>
<td>Generic function for the computation of a risk for an IC</td></tr>
-<tr><td width="25%"><a href="GumbelLocationFamily.html">GumbelLocationFamily</a></td>
-<td>Generating function for Gumbel location families</td></tr>
</table>
-<h2><a name="I">-- I --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="IC.html">IC</a></td>
-<td>Generating function for IC-class</td></tr>
-<tr><td width="25%"><a href="IC-class.html">IC-class</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve.html">InfluenceCurve</a></td>
-<td>Generating function for InfluenceCurve-class</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="infoPlot.html">infoPlot</a></td>
-<td>Plot absolute and relative information</td></tr>
-<tr><td width="25%"><a href="IC-class.html">infoPlot,IC-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Infos</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Infos,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Infos<-,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfRobModel.html">InfRobModel</a></td>
-<td>Generating function for InfRobModel-class</td></tr>
-<tr><td width="25%"><a href="InfRobModel-class.html">InfRobModel-class</a></td>
-<td>Robust model with infinitesimal (unconditional) neighborhood</td></tr>
-</table>
-
-<h2><a name="K">-- K --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Binom-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Exp-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Gammad-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Gumbel-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Lnorm-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Norm-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator,numeric,Pois-method</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-<tr><td width="25%"><a href="ksEstimator.html">ksEstimator-methods</a></td>
-<td>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</td></tr>
-</table>
-
<h2><a name="L">-- L --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2deriv</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2deriv,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2derivDistr</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2derivDistr,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2derivDistrSymm</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2derivDistrSymm,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2derivSymm</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2derivSymm,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily.html">L2ParamFamily</a></td>
-<td>Generating function for L2ParamFamily-class</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></td>
-<td>L2 differentiable parametric family</td></tr>
<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius</a></td>
<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method</a></td>
<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius-methods</a></td>
<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">length,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="LnormScaleFamily.html">LnormScaleFamily</a></td>
-<td>Generating function for lognormal scale families</td></tr>
<tr><td width="25%"><a href="locMEstimator.html">locMEstimator</a></td>
<td>Generic function for the computation of location M estimators</td></tr>
<tr><td width="25%"><a href="locMEstimator.html">locMEstimator,numeric,InfluenceCurve-method</a></td>
<td>Generic function for the computation of location M estimators</td></tr>
<tr><td width="25%"><a href="locMEstimator.html">locMEstimator-methods</a></td>
<td>Generic function for the computation of location M estimators</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">lowerCase</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">lowerCase,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">lowerCase,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">lowerCase<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">lowerCase<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius</a></td>
<td>Computation of the lower case radius</td></tr>
-<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE-method</a></td>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method</a></td>
<td>Computation of the lower case radius</td></tr>
-<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE-method</a></td>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method</a></td>
<td>Computation of the lower case radius</td></tr>
<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius-methods</a></td>
<td>Computation of the lower case radius</td></tr>
@@ -527,110 +242,23 @@
<h2><a name="M">-- M --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="ParamFamParameter-class.html">main</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="ParamFamily-class.html">main,ParamFamily-method</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">main,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">main<-,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Map,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias-methods</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
</table>
-<h2><a name="N">-- N --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="BiasType-class.html">name,BiasType-method</a></td>
-<td>Bias Type</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">name,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">name,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">name,RobModel-method</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="BiasType-class.html">name<-,BiasType-method</a></td>
-<td>Bias Type</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">name<-,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">name<-,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="negativeBias.html">negativeBias</a></td>
-<td>Generating function for onesidedBiasType-class</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">neighbor</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">neighbor,RobModel-method</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="FixRobModel-class.html">neighbor<-,FixRobModel-method</a></td>
-<td>Robust model with fixed (unconditional) neighborhood</td></tr>
-<tr><td width="25%"><a href="InfRobModel-class.html">neighbor<-,InfRobModel-method</a></td>
-<td>Robust model with infinitesimal (unconditional) neighborhood</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">neighbor<-,RobModel-method</a></td>
-<td>Robust model</td></tr>
-<tr><td width="25%"><a href="Neighborhood-class.html">Neighborhood-class</a></td>
-<td>Neighborhood</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">neighborRadius</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">neighborRadius,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">neighborRadius,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">neighborRadius<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">neighborRadius<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="NonSymmetric.html">NonSymmetric</a></td>
-<td>Generating function for NonSymmetric-class</td></tr>
-<tr><td width="25%"><a href="NonSymmetric-class.html">NonSymmetric-class</a></td>
-<td>Class for Non-symmetric Functions</td></tr>
-<tr><td width="25%"><a href="NormLocationFamily.html">NormLocationFamily</a></td>
-<td>Generating function for normal location families</td></tr>
-<tr><td width="25%"><a href="NormLocationScaleFamily.html">NormLocationScaleFamily</a></td>
-<td>Generating function for normal location and scale families</td></tr>
-<tr><td width="25%"><a href="NormScaleFamily.html">NormScaleFamily</a></td>
-<td>Generating function for normal scale families</td></tr>
-<tr><td width="25%"><a href="NoSymmetry.html">NoSymmetry</a></td>
-<td>Generating function for NoSymmetry-class</td></tr>
-<tr><td width="25%"><a href="NoSymmetry-class.html">NoSymmetry-class</a></td>
-<td>Class for Non-symmetric Distributions</td></tr>
-<tr><td width="25%"><a href="asymmetricBiasType-class.html">nu</a></td>
-<td>asymmetric Bias Type</td></tr>
-<tr><td width="25%"><a href="asymmetricBiasType-class.html">nu,asymmetricBiasType-method</a></td>
-<td>asymmetric Bias Type</td></tr>
-<tr><td width="25%"><a href="asymmetricBiasType-class.html">nu<-,asymmetricBiasType-method</a></td>
-<td>asymmetric Bias Type</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">nuisance</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="ParamFamily-class.html">nuisance,ParamFamily-method</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">nuisance,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">nuisance<-,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-</table>
-
<h2><a name="O">-- O --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="OddSymmetric.html">OddSymmetric</a></td>
-<td>Generating function for OddSymmetric-class</td></tr>
-<tr><td width="25%"><a href="OddSymmetric-class.html">OddSymmetric-class</a></td>
-<td>Class for Odd Functions</td></tr>
-<tr><td width="25%"><a href="onesidedBiasType-class.html">onesidedBiasType-class</a></td>
-<td>onesided Bias Type</td></tr>
-<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator</a></td>
-<td>Generic function for the computation of one-step estimators</td></tr>
-<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,matrix,InfluenceCurve,list-method</a></td>
-<td>Generic function for the computation of one-step estimators</td></tr>
-<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,matrix,InfluenceCurve,numeric-method</a></td>
-<td>Generic function for the computation of one-step estimators</td></tr>
-<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,numeric,InfluenceCurve,list-method</a></td>
-<td>Generic function for the computation of one-step estimators</td></tr>
-<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,numeric,InfluenceCurve,numeric-method</a></td>
-<td>Generic function for the computation of one-step estimators</td></tr>
-<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator-methods</a></td>
-<td>Generic function for the computation of one-step estimators</td></tr>
<tr><td width="25%"><a href="optIC.html">optIC</a></td>
<td>Generic function for the computation of optimally robust ICs</td></tr>
<tr><td width="25%"><a href="optIC.html">optIC,FixRobModel,fiUnOvShoot-method</a></td>
@@ -643,8 +271,6 @@
<td>Generic function for the computation of optimally robust ICs</td></tr>
<tr><td width="25%"><a href="optIC.html">optIC-methods</a></td>
<td>Generic function for the computation of optimally robust ICs</td></tr>
-<tr><td width="25%"><a href="OptionalNumeric-class.html">OptionalNumeric-class</a></td>
-<td>Optional numeric</td></tr>
<tr><td width="25%"><a href="optRisk.html">optRisk</a></td>
<td>Generic function for the computation of the minimal risk</td></tr>
<tr><td width="25%"><a href="optRisk.html">optRisk,FixRobModel,fiUnOvShoot-method</a></td>
@@ -657,187 +283,23 @@
<td>Generic function for the computation of the minimal risk</td></tr>
</table>
-<h2><a name="P">-- P --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="ParamFamily-class.html">param,ParamFamily-method</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="ParamFamily.html">ParamFamily</a></td>
-<td>Generating function for ParamFamily-class</td></tr>
-<tr><td width="25%"><a href="ParamFamily-class.html">ParamFamily-class</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter.html">ParamFamParameter</a></td>
-<td>Generating function for ParamFamParameter-class</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">ParamFamParameter-class</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="IC-class.html">plot,IC-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="L2ParamFamily-class.html">plot,L2ParamFamily-method</a></td>
-<td>L2 differentiable parametric family</td></tr>
-<tr><td width="25%"><a href="ParamFamily-class.html">plot,ParamFamily-method</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="PoisFamily.html">PoisFamily</a></td>
-<td>Generating function for Poisson families</td></tr>
-<tr><td width="25%"><a href="PosDefSymmMatrix.html">PosDefSymmMatrix</a></td>
-<td>Generating function for PosDefSymmMatrix-class</td></tr>
-<tr><td width="25%"><a href="PosDefSymmMatrix-class.html">PosDefSymmMatrix-class</a></td>
-<td>Positive-definite, symmetric matrices</td></tr>
-<tr><td width="25%"><a href="positiveBias.html">positiveBias</a></td>
-<td>Generating function for onesidedBiasType-class</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">ProbFamily-class</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">props</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">props,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-<tr><td width="25%"><a href="ProbFamily-class.html">props<-,ProbFamily-method</a></td>
-<td>Family of probability measures</td></tr>
-</table>
-
<h2><a name="R">-- R --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="Neighborhood-class.html">radius</a></td>
-<td>Neighborhood</td></tr>
-<tr><td width="25%"><a href="Neighborhood-class.html">radius,Neighborhood-method</a></td>
-<td>Neighborhood</td></tr>
<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC</a></td>
<td>Generic function for the computation of the radius minimax IC</td></tr>
<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method</a></td>
<td>Generic function for the computation of the radius minimax IC</td></tr>
<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC-methods</a></td>
<td>Generic function for the computation of the radius minimax IC</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Range,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Risks</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Risks,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">Risks<-,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="RiskType-class.html">RiskType-class</a></td>
-<td>Risk</td></tr>
-<tr><td width="25%"><a href="RobModel-class.html">RobModel-class</a></td>
-<td>Robust model</td></tr>
</table>
-<h2><a name="S">-- S --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="asHampel-class.html">show,asHampel-method</a></td>
-<td>Asymptotic Hampel risk</td></tr>
-<tr><td width="25%"><a href="asUnOvShoot-class.html">show,asUnOvShoot-method</a></td>
-<td>Asymptotic under-/overshoot probability</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">show,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="fiHampel-class.html">show,fiHampel-method</a></td>
-<td>Finite-sample Hampel risk</td></tr>
-<tr><td width="25%"><a href="fiUnOvShoot-class.html">show,fiUnOvShoot-method</a></td>
-<td>Finite-sample under-/overshoot probability</td></tr>
-<tr><td width="25%"><a href="FixRobModel-class.html">show,FixRobModel-method</a></td>
-<td>Robust model with fixed (unconditional) neighborhood</td></tr>
-<tr><td width="25%"><a href="IC-class.html">show,IC-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfluenceCurve-class.html">show,InfluenceCurve-method</a></td>
-<td>Influence curve</td></tr>
-<tr><td width="25%"><a href="InfRobModel-class.html">show,InfRobModel-method</a></td>
-<td>Robust model with infinitesimal (unconditional) neighborhood</td></tr>
-<tr><td width="25%"><a href="Neighborhood-class.html">show,Neighborhood-method</a></td>
-<td>Neighborhood</td></tr>
-<tr><td width="25%"><a href="ParamFamily-class.html">show,ParamFamily-method</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">show,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="RiskType-class.html">show,RiskType-method</a></td>
-<td>Risk</td></tr>
-<tr><td width="25%"><a href="Symmetry-class.html">show,Symmetry-method</a></td>
-<td>Class of Symmetries</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">show,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="onesidedBiasType-class.html">sign</a></td>
-<td>onesided Bias Type</td></tr>
-<tr><td width="25%"><a href="onesidedBiasType-class.html">sign,onesidedBiasType-method</a></td>
-<td>onesided Bias Type</td></tr>
-<tr><td width="25%"><a href="onesidedBiasType-class.html">sign<-,onesidedBiasType-method</a></td>
-<td>onesided Bias Type</td></tr>
-<tr><td width="25%"><a href="SphericalSymmetry.html">SphericalSymmetry</a></td>
-<td>Generating function for SphericalSymmetry-class</td></tr>
-<tr><td width="25%"><a href="SphericalSymmetry-class.html">SphericalSymmetry-class</a></td>
-<td>Class for Spherical Symmetric Distributions</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">stand</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">stand,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">stand,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="ContIC-class.html">stand<-,ContIC-method</a></td>
-<td>Influence curve of contamination type</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">stand<-,TotalVarIC-method</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="Symmetry-class.html">SymmCenter</a></td>
-<td>Class of Symmetries</td></tr>
-<tr><td width="25%"><a href="Symmetry-class.html">SymmCenter,Symmetry-method</a></td>
-<td>Class of Symmetries</td></tr>
-<tr><td width="25%"><a href="symmetricBias.html">symmetricBias</a></td>
-<td>Generating function for symmetricBias-class</td></tr>
-<tr><td width="25%"><a href="symmetricBiasType-class.html">symmetricBiasType-class</a></td>
-<td>symmetric Bias Type</td></tr>
-<tr><td width="25%"><a href="Symmetry-class.html">Symmetry-class</a></td>
-<td>Class of Symmetries</td></tr>
-</table>
-
<h2><a name="T">-- T --</a></h2>
<table width="100%">
-<tr><td width="25%"><a href="TotalVarIC.html">TotalVarIC</a></td>
-<td>Generating function for TotalVarIC-class</td></tr>
-<tr><td width="25%"><a href="TotalVarIC-class.html">TotalVarIC-class</a></td>
-<td>Influence curve of total variation type</td></tr>
-<tr><td width="25%"><a href="TotalVarNeighborhood.html">TotalVarNeighborhood</a></td>
-<td>Generating function for TotalVarNeighborhood-class</td></tr>
-<tr><td width="25%"><a href="TotalVarNeighborhood-class.html">TotalVarNeighborhood-class</a></td>
-<td>Total variation neighborhood</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">trafo</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="ParamFamily-class.html">trafo,ParamFamily-method</a></td>
-<td>Parametric family of probability measures.</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">trafo,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="ParamFamParameter-class.html">trafo<-,ParamFamParameter-method</a></td>
-<td>Parameter of a parametric family of probability measures</td></tr>
-<tr><td width="25%"><a href="trAsCov.html">trAsCov</a></td>
-<td>Generating function for trAsCov-class</td></tr>
<tr><td width="25%"><a href="trAsCov-class.html">trAsCov-class</a></td>
<td>Trace of asymptotic covariance</td></tr>
-<tr><td width="25%"><a href="trFiCov.html">trFiCov</a></td>
-<td>Generating function for trFiCov-class</td></tr>
<tr><td width="25%"><a href="trFiCov-class.html">trFiCov-class</a></td>
<td>Trace of finite-sample covariance</td></tr>
-<tr><td width="25%"><a href="Symmetry-class.html">type</a></td>
-<td>Class of Symmetries</td></tr>
-<tr><td width="25%"><a href="Neighborhood-class.html">type,Neighborhood-method</a></td>
-<td>Neighborhood</td></tr>
-<tr><td width="25%"><a href="RiskType-class.html">type,RiskType-method</a></td>
-<td>Risk</td></tr>
-<tr><td width="25%"><a href="Symmetry-class.html">type,Symmetry-method</a></td>
-<td>Class of Symmetries</td></tr>
</table>
-
-<h2><a name="U">-- U --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></td>
-<td>Unconditional neighborhood</td></tr>
-</table>
-
-<h2><a name="W">-- W --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="asUnOvShoot-class.html">width</a></td>
-<td>Asymptotic under-/overshoot probability</td></tr>
-<tr><td width="25%"><a href="asUnOvShoot-class.html">width,asUnOvShoot-method</a></td>
-<td>Asymptotic under-/overshoot probability</td></tr>
-<tr><td width="25%"><a href="fiUnOvShoot-class.html">width,fiUnOvShoot-method</a></td>
-<td>Finite-sample under-/overshoot probability</td></tr>
-</table>
</body></html>
Deleted: pkg/ROptEst/chm/BiasType-class.html
===================================================================
--- pkg/ROptEst/chm/BiasType-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/BiasType-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,87 +0,0 @@
-<html><head><title>Bias Type</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>BiasType-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: BiasType-class">
-<param name="keyword" value="R: name,BiasType-method">
-<param name="keyword" value="R: name<-,BiasType-method">
-<param name="keyword" value=" Bias Type">
-</object>
-
-
-<h2>Bias Type</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of bias types.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>.</dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>name</dt><dd><code>signature(object = "BiasType")</code>:
-accessor function for slot <code>name</code>. </dd>
-<dt>name<-</dt><dd><code>signature(object = "BiasType", value = "character")</code>:
-replacement function for slot <code>name</code>. </dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="RiskType-class.html">RiskType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-aB <- positiveBias()
-name(aB)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/BinomFamily.html
===================================================================
--- pkg/ROptEst/chm/BinomFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/BinomFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,103 +0,0 @@
-<html><head><title>Generating function for Binomial families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>BinomFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: BinomFamily">
-<param name="keyword" value=" Generating function for Binomial families">
-</object>
-
-
-<h2>Generating function for Binomial families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a Binomial family where the probability of
-success is the parameter of interest.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-BinomFamily(size = 1, prob = 0.5, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>size</code></td>
-<td>
-number of trials </td></tr>
-<tr valign="top"><td><code>prob</code></td>
-<td>
-probability of success </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the
-Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Binom-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Binom-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(B1 <- BinomFamily(size = 25, prob = 0.25))
-plot(B1)
-FisherInfo(B1)
-checkL2deriv(B1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ContIC-class.html
===================================================================
--- pkg/ROptEst/chm/ContIC-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ContIC-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,203 +0,0 @@
-<html><head><title>Influence curve of contamination type</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ContIC-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ContIC-class">
-<param name="keyword" value="R: CallL2Fam<-,ContIC-method">
-<param name="keyword" value="R: cent">
-<param name="keyword" value="R: cent,ContIC-method">
-<param name="keyword" value="R: cent<-">
-<param name="keyword" value="R: cent<-,ContIC-method">
-<param name="keyword" value="R: clip">
-<param name="keyword" value="R: clip,ContIC-method">
-<param name="keyword" value="R: clip<-">
-<param name="keyword" value="R: clip<-,ContIC-method">
-<param name="keyword" value="R: lowerCase">
-<param name="keyword" value="R: lowerCase,ContIC-method">
-<param name="keyword" value="R: lowerCase<-">
-<param name="keyword" value="R: lowerCase<-,ContIC-method">
-<param name="keyword" value="R: neighborRadius">
-<param name="keyword" value="R: neighborRadius,ContIC-method">
-<param name="keyword" value="R: neighborRadius<-">
-<param name="keyword" value="R: neighborRadius<-,ContIC-method">
-<param name="keyword" value="R: stand">
-<param name="keyword" value="R: stand,ContIC-method">
-<param name="keyword" value="R: stand<-">
-<param name="keyword" value="R: stand<-,ContIC-method">
-<param name="keyword" value="R: generateIC,ContNeighborhood,L2ParamFamily-method">
-<param name="keyword" value="R: show,ContIC-method">
-<param name="keyword" value=" Influence curve of contamination type">
-</object>
-
-
-<h2>Influence curve of contamination type</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of (partial) influence curves of contamination type;
-i.e., influence curves <i>eta</i> of the form
-</p><p align="center"><i>eta = (A Lambda - a)min(1, b/|A Lambda - a|)</i></p><p>
-with clipping bound <i>b</i>, centering constant <i>a</i> and
-standardizing matrix <i>A</i>. <i>Lambda</i> stands for
-the L2 derivative of the corresponding L2 differentiable
-parametric family created via the call in the slot <code>CallL2Fam</code>.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("ContIC", ...)</code>.
-More frequently they are created via the generating function
-<code>ContIC</code>, respectively via the method <code>generateIC</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>CallL2Fam</code>:</dt><dd>object of class <code>"call"</code>:
-creates an object of the underlying L2-differentiable
-parametric family. </dd>
-
-
-<dt><code>name</code>:</dt><dd>object of class <code>"character"</code> </dd>
-
-
-<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code></dd>
-
-
-<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </dd>
-
-
-<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
-with two columns named <code>method</code> and <code>message</code>:
-additional informations. </dd>
-
-
-<dt><code>clip</code>:</dt><dd>object of class <code>"numeric"</code>:
-clipping bound. </dd>
-
-
-<dt><code>cent</code>:</dt><dd>object of class <code>"numeric"</code>:
-centering constant. </dd>
-
-
-<dt><code>stand</code>:</dt><dd>object of class <code>"matrix"</code>:
-standardizing matrix. </dd>
-
-
-<dt><code>lowerCase</code>:</dt><dd>object of class <code>"OptionalNumeric"</code>:
-optional constant for lower case solution. </dd>
-
-
-<dt><code>neighborRadius</code>:</dt><dd>object of class <code>"numeric"</code>:
-radius of the corresponding (unconditional) contamination
-neighborhood. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"IC"</code>, directly.<br>
-Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>CallL2Fam<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>CallL2Fam</code>. </dd>
-
-
-<dt>cent</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>cent</code>. </dd>
-
-
-<dt>cent<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>cent</code>. </dd>
-
-
-<dt>clip</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>clip</code>. </dd>
-
-
-<dt>clip<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>clip</code>. </dd>
-
-
-<dt>stand</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>stand</code>. </dd>
-
-
-<dt>stand<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>stand</code>. </dd>
-
-
-<dt>lowerCase</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>lowerCase</code>. </dd>
-
-
-<dt>lowerCase<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>lowerCase</code>. </dd>
-
-
-<dt>neighborRadius</dt><dd><code>signature(object = "ContIC")</code>:
-accessor function for slot <code>neighborRadius</code>. </dd>
-
-
-<dt>neighborRadius<-</dt><dd><code>signature(object = "ContIC")</code>:
-replacement function for slot <code>neighborRadius</code>. </dd>
-
-
-<dt>generateIC</dt><dd><code>signature(neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily")</code>:
-generate an object of class <code>"ContIC"</code>. Rarely called directly. </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "ContIC")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- new("ContIC")
-plot(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ContIC.html
===================================================================
--- pkg/ROptEst/chm/ContIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ContIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,121 +0,0 @@
-<html><head><title>Generating function for ContIC-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ContIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ContIC">
-<param name="keyword" value=" Generating function for ContIC-class">
-</object>
-
-
-<h2>Generating function for ContIC-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"ContIC"</code>;
-i.e., an influence curves <i>eta</i> of the form
-</p><p align="center"><i>eta = (A Lambda - a)min(1, b/|A Lambda - a|)</i></p><p>
-with clipping bound <i>b</i>, centering constant <i>a</i> and
-standardizing matrix <i>A</i>. <i>Lambda</i> stands for
-the L2 derivative of the corresponding L2 differentiable
-parametric family which can be created via <code>CallL2Fam</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-ContIC(name, CallL2Fam = call("L2ParamFamily"),
- Curve = EuclRandVarList(RealRandVariable(Map = c(function(x){x}),
- Domain = Reals())),
- Risks, Infos, clip = Inf, cent = 0, stand = as.matrix(1),
- lowerCase = NULL, neighborRadius = 0)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-object of class <code>"character"</code>. </td></tr>
-<tr valign="top"><td><code>CallL2Fam</code></td>
-<td>
-object of class <code>"call"</code>:
-creates an object of the underlying L2-differentiable
-parametric family. </td></tr>
-<tr valign="top"><td><code>Curve</code></td>
-<td>
-object of class <code>"EuclRandVarList"</code> </td></tr>
-<tr valign="top"><td><code>Risks</code></td>
-<td>
-object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </td></tr>
-<tr valign="top"><td><code>Infos</code></td>
-<td>
-matrix of characters with two columns
-named <code>method</code> and <code>message</code>: additional informations. </td></tr>
-<tr valign="top"><td><code>clip</code></td>
-<td>
-positive real: clipping bound. </td></tr>
-<tr valign="top"><td><code>cent</code></td>
-<td>
-real: centering constant </td></tr>
-<tr valign="top"><td><code>stand</code></td>
-<td>
-matrix: standardizing matrix </td></tr>
-<tr valign="top"><td><code>lowerCase</code></td>
-<td>
-optional constant for lower case solution. </td></tr>
-<tr valign="top"><td><code>neighborRadius</code></td>
-<td>
-radius of the corresponding (unconditional)
-contamination neighborhood. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"ContIC"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- ContIC()
-plot(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ContNeighborhood-class.html
===================================================================
--- pkg/ROptEst/chm/ContNeighborhood-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ContNeighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,93 +0,0 @@
-<html><head><title>Contamination Neighborhood</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ContNeighborhood-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ContNeighborhood-class">
-<param name="keyword" value=" Contamination Neighborhood">
-</object>
-
-
-<h2>Contamination Neighborhood</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of (unconditional) contamination neighborhoods.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("ContNeighborhood", ...)</code>.
-More frequently they are created via the generating function
-<code>ContNeighborhood</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“(uncond.) convex contamination neighborhood”. </dd>
-
-
-<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
-neighborhood radius. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"UncondNeighborhood"</code>, directly.<br>
-Class <code>"Neighborhood"</code>, by class <code>"UncondNeighborhood"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "ContNeighborhood" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ContNeighborhood.html">ContNeighborhood</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("ContNeighborhood")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ContNeighborhood.html
===================================================================
--- pkg/ROptEst/chm/ContNeighborhood.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ContNeighborhood.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,81 +0,0 @@
-<html><head><title>Generating function for ContNeighborhood-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ContNeighborhood(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ContNeighborhood">
-<param name="keyword" value=" Generating function for ContNeighborhood-class">
-</object>
-
-
-<h2>Generating function for ContNeighborhood-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"ContNeighborhood"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>ContNeighborhood(radius = 0)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>radius</code></td>
-<td>
-non-negative real: neighborhood radius. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"ContNeighborhood"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ContNeighborhood-class.html">ContNeighborhood-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-ContNeighborhood()
-
-## The function is currently defined as
-function(radius = 0){
- new("ContNeighborhood", radius = radius)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/DistrSymmList-class.html
===================================================================
--- pkg/ROptEst/chm/DistrSymmList-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/DistrSymmList-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,72 +0,0 @@
-<html><head><title>List of Symmetries for a List of Distributions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>DistrSymmList-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: DistrSymmList-class">
-<param name="keyword" value=" List of Symmetries for a List of Distributions">
-</object>
-
-
-<h2>List of Symmetries for a List of Distributions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Create a list of symmetries for a list of distributions
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("DistrSymmList", ...)</code>.
-More frequently they are created via the generating function
-<code>DistrSymmList</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>.Data</code>:</dt><dd>Object of class <code>"list"</code>. A list
-of objects of class <code>"DistributionSymmetry"</code>. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"list"</code>, from data part.<br>
-Class <code>"vector"</code>, by class <code>"list"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("DistrSymmList", list(NoSymmetry(), SphericalSymmetry(SymmCenter = 1),
- EllipticalSymmetry(SymmCenter = 2)))
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/DistrSymmList.html
===================================================================
--- pkg/ROptEst/chm/DistrSymmList.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/DistrSymmList.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,74 +0,0 @@
-<html><head><title>Generating function for DistrSymmList-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>DistrSymmList(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: DistrSymmList">
-<param name="keyword" value=" Generating function for DistrSymmList-class">
-</object>
-
-
-<h2>Generating function for DistrSymmList-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"DistrSymmList"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-DistrSymmList(...)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>...</code></td>
-<td>
-Objects of class <code>"DistributionSymmetry"</code> which
-shall form the list of symmetry types. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"DistrSymmList"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="DistrSymmList-class.html">DistrSymmList-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-DistrSymmList(NoSymmetry(), SphericalSymmetry(SymmCenter = 1),
- EllipticalSymmetry(SymmCenter = 2))
-
-## The function is currently defined as
-function (...){
- new("DistrSymmList", list(...))
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/DistributionSymmetry-class.html
===================================================================
--- pkg/ROptEst/chm/DistributionSymmetry-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/DistributionSymmetry-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,73 +0,0 @@
-<html><head><title>Class of Symmetries for Distributions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>DistributionSymmetry-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: DistributionSymmetry-class">
-<param name="keyword" value=" Class of Symmetries for Distributions">
-</object>
-
-
-<h2>Class of Symmetries for Distributions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of symmetries for distributions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-discribes type of symmetry. </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"OptionalNumeric"</code>:
-center of symmetry. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"Symmetry"</code>, directly.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="Symmetry-class.html">Symmetry-class</a></code>, <code><a onclick="findlink('distr', 'Distribution-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Distribution-class</a></code>,
-<code><a href="OptionalNumeric-class.html">OptionalNumeric-class</a></code>
-</p>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/EllipticalSymmetry-class.html
===================================================================
--- pkg/ROptEst/chm/EllipticalSymmetry-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/EllipticalSymmetry-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,74 +0,0 @@
-<html><head><title>Class for Elliptically Symmetric Distributions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>EllipticalSymmetry-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: EllipticalSymmetry-class">
-<param name="keyword" value=" Class for Elliptically Symmetric Distributions">
-</object>
-
-
-<h2>Class for Elliptically Symmetric Distributions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class for elliptically symmetric distributions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("EllipticalSymmetry")</code>.
-More frequently they are created via the generating function
-<code>EllipticalSymmetry</code>. Elliptical symmetry for instance leads to
-a simplification for the computation of optimally robust influence curves.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-contains “elliptical symmetric distribution” </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"numeric"</code>:
-center of symmetry </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"DistributionSymmetry"</code>, directly.<br>
-Class <code>"Symmetry"</code>, by class <code>"DistributionSymmetry"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="EllipticalSymmetry.html">EllipticalSymmetry</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("EllipticalSymmetry")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/EllipticalSymmetry.html
===================================================================
--- pkg/ROptEst/chm/EllipticalSymmetry.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/EllipticalSymmetry.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,70 +0,0 @@
-<html><head><title>Generating function for EllipticalSymmetry-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>EllipticalSymmetry(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: EllipticalSymmetry">
-<param name="keyword" value=" Generating function for EllipticalSymmetry-class">
-</object>
-
-
-<h2>Generating function for EllipticalSymmetry-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"EllipticalSymmetry"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>EllipticalSymmetry(SymmCenter = 0)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>SymmCenter</code></td>
-<td>
-numeric: center of symmetry </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"EllipticalSymmetry"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="EllipticalSymmetry-class.html">EllipticalSymmetry-class</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-EllipticalSymmetry()
-
-## The function is currently defined as
-function(SymmCenter = 0){
- new("EllipticalSymmetry", SymmCenter = SymmCenter)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/EvenSymmetric-class.html
===================================================================
--- pkg/ROptEst/chm/EvenSymmetric-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/EvenSymmetric-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,73 +0,0 @@
-<html><head><title>Class for Even Functions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>EvenSymmetric-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: EvenSymmetric-class">
-<param name="keyword" value=" Class for Even Functions">
-</object>
-
-
-<h2>Class for Even Functions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class for even functions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("EvenSymmetric")</code>.
-More frequently they are created via the generating function
-<code>EvenSymmetric</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-contains “even function” </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"numeric"</code>:
-center of symmetry </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"FunctionSymmetry"</code>, directly.<br>
-Class <code>"Symmetry"</code>, by class <code>"FunctionSymmetry"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="EvenSymmetric.html">EvenSymmetric</a></code>, <code><a href="FunctionSymmetry-class.html">FunctionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("EvenSymmetric")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/EvenSymmetric.html
===================================================================
--- pkg/ROptEst/chm/EvenSymmetric.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/EvenSymmetric.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,70 +0,0 @@
-<html><head><title>Generating function for EvenSymmetric-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>EvenSymmetric(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: EvenSymmetric">
-<param name="keyword" value=" Generating function for EvenSymmetric-class">
-</object>
-
-
-<h2>Generating function for EvenSymmetric-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"EvenSymmetric"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>EvenSymmetric(SymmCenter = 0)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>SymmCenter</code></td>
-<td>
-numeric: center of symmetry </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"EvenSymmetric"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="EvenSymmetric-class.html">EvenSymmetric-class</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-EvenSymmetric()
-
-## The function is currently defined as
-function(SymmCenter = 0){
- new("EvenSymmetric", SymmCenter = SymmCenter)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ExpScaleFamily.html
===================================================================
--- pkg/ROptEst/chm/ExpScaleFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ExpScaleFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,100 +0,0 @@
-<html><head><title>Generating function for exponential scale families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ExpScaleFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ExpScaleFamily">
-<param name="keyword" value=" Generating function for exponential scale families">
-</object>
-
-
-<h2>Generating function for exponential scale families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents an exponential scale family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-ExpScaleFamily(rate = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>rate</code></td>
-<td>
-rate </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: optional transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled. The scale parameter corresponds
-to <i>1/<code>rate</code></i>.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Exp-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Exp-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(E1 <- ExpScaleFamily())
-plot(E1)
-Map(L2deriv(E1)[[1]])
-checkL2deriv(E1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/FixRobModel-class.html
===================================================================
--- pkg/ROptEst/chm/FixRobModel-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/FixRobModel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,94 +0,0 @@
-<html><head><title>Robust model with fixed (unconditional) neighborhood</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>FixRobModel-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: FixRobModel-class">
-<param name="keyword" value="R: neighbor<-,FixRobModel-method">
-<param name="keyword" value="R: show,FixRobModel-method">
-<param name="keyword" value=" Robust model with fixed (unconditional) neighborhood">
-</object>
-
-
-<h2>Robust model with fixed (unconditional) neighborhood</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of robust models with fixed (unconditional) neighborhoods.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("FixRobModel", ...)</code>.
-More frequently they are created via the generating function
-<code>FixRobModel</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>center</code>:</dt><dd>Object of class <code>"ProbFamily"</code>. </dd>
-<dt><code>neighbor</code>:</dt><dd>Object of class <code>"UncondNeighborhood"</code>.</dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"RobModel"</code>, directly.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>neighbor<-</dt><dd><code>signature(object = "FixRobModel")</code>:
-replacement function for slot <code>neighbor<-</code> </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "FixRobModel")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ProbFamily-class.html">ProbFamily-class</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>,
-<code><a href="FixRobModel.html">FixRobModel</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("FixRobModel")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/FixRobModel.html
===================================================================
--- pkg/ROptEst/chm/FixRobModel.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/FixRobModel.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-<html><head><title>Generating function for FixRobModel-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>FixRobModel(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: FixRobModel">
-<param name="keyword" value=" Generating function for FixRobModel-class">
-</object>
-
-
-<h2>Generating function for FixRobModel-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"FixRobModel"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-FixRobModel(center = ParamFamily(), neighbor = ContNeighborhood())
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>center</code></td>
-<td>
-object of class <code>"ProbFamily"</code> </td></tr>
-<tr valign="top"><td><code>neighbor</code></td>
-<td>
-object of class <code>"UncondNeighborhood"</code> </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"FixRobModel"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="FixRobModel-class.html">FixRobModel-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(M1 <- FixRobModel())
-
-## The function is currently defined as
-function(center = ParamFamily(), neighbor = ContNeighborhood()){
- new("FixRobModel", center = center, neighbor = neighbor)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/FunSymmList-class.html
===================================================================
--- pkg/ROptEst/chm/FunSymmList-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/FunSymmList-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,72 +0,0 @@
-<html><head><title>List of Symmetries for a List of Functions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>FunSymmList-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: FunSymmList-class">
-<param name="keyword" value=" List of Symmetries for a List of Functions">
-</object>
-
-
-<h2>List of Symmetries for a List of Functions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Create a list of symmetries for a list of functions
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("FunSymmList", ...)</code>.
-More frequently they are created via the generating function
-<code>FunSymmList</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>.Data</code>:</dt><dd>Object of class <code>"list"</code>. A list
-of objects of class <code>"FunctionSymmetry"</code>. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"list"</code>, from data part.<br>
-Class <code>"vector"</code>, by class <code>"list"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="FunctionSymmetry-class.html">FunctionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("FunSymmList", list(NonSymmetric(), EvenSymmetric(SymmCenter = 1),
- OddSymmetric(SymmCenter = 2)))
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/FunSymmList.html
===================================================================
--- pkg/ROptEst/chm/FunSymmList.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/FunSymmList.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,74 +0,0 @@
-<html><head><title>Generating function for FunSymmList-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>FunSymmList(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: FunSymmList">
-<param name="keyword" value=" Generating function for FunSymmList-class">
-</object>
-
-
-<h2>Generating function for FunSymmList-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"FunSymmList"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-FunSymmList(...)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>...</code></td>
-<td>
-Objects of class <code>"FunctionSymmetry"</code> which
-shall form the list of symmetry types. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"FunSymmList"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="FunSymmList-class.html">FunSymmList-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-FunSymmList(NonSymmetric(), EvenSymmetric(SymmCenter = 1),
- OddSymmetric(SymmCenter = 2))
-
-## The function is currently defined as
-function (...){
- new("FunSymmList", list(...))
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/FunctionSymmetry-class.html
===================================================================
--- pkg/ROptEst/chm/FunctionSymmetry-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/FunctionSymmetry-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,63 +0,0 @@
-<html><head><title>Class of Symmetries for Functions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>FunctionSymmetry-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: FunctionSymmetry-class">
-<param name="keyword" value=" Class of Symmetries for Functions">
-</object>
-
-
-<h2>Class of Symmetries for Functions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of symmetries for functions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-discribes type of symmetry. </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"OptionalNumeric"</code>:
-center of symmetry. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"Symmetry"</code>, directly.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="Symmetry-class.html">Symmetry-class</a></code>, <code><a href="OptionalNumeric-class.html">OptionalNumeric-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/GammaFamily.html
===================================================================
--- pkg/ROptEst/chm/GammaFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/GammaFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,103 +0,0 @@
-<html><head><title>Generating function for Gamma families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>GammaFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: GammaFamily">
-<param name="keyword" value=" Generating function for Gamma families">
-</object>
-
-
-<h2>Generating function for Gamma families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a Gamma family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-GammaFamily(scale = 1, shape = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>scale</code></td>
-<td>
-positive real: scale parameter </td></tr>
-<tr valign="top"><td><code>shape</code></td>
-<td>
-positive real: shape parameter </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Gamma-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Gamma-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-distrExOptions("EupperTruncQuantile" = 1e-15) # problem with q(Gamma())(1) = NaN
-(G1 <- GammaFamily())
-FisherInfo(G1)
-checkL2deriv(G1)
-distrExOptions("EupperTruncQuantile" = 0) # default
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/GumbelLocationFamily.html
===================================================================
--- pkg/ROptEst/chm/GumbelLocationFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/GumbelLocationFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,105 +0,0 @@
-<html><head><title>Generating function for Gumbel location families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>GumbelLocationFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: GumbelLocationFamily">
-<param name="keyword" value=" Generating function for Gumbel location families">
-</object>
-
-
-<h2>Generating function for Gumbel location families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a Gumbel location family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-GumbelLocationFamily(loc = 0, scale = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>loc</code></td>
-<td>
-location parameter </td></tr>
-<tr valign="top"><td><code>scale</code></td>
-<td>
-scale parameter </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distrEx', 'Gumbel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Gumbel-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-distrExOptions("ElowerTruncQuantile" = 1e-15) # problem with
- # non-finite function value
-(G1 <- GumbelLocationFamily())
-plot(G1)
-Map(L2deriv(G1)[[1]])
-checkL2deriv(G1)
-distrExOptions("ElowerTruncQuantile" = 0) # default
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/IC-class.html
===================================================================
--- pkg/ROptEst/chm/IC-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/IC-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,145 +0,0 @@
-<html><head><title>Influence curve</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>IC-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: IC-class">
-<param name="keyword" value="R: CallL2Fam">
-<param name="keyword" value="R: CallL2Fam,IC-method">
-<param name="keyword" value="R: CallL2Fam<-">
-<param name="keyword" value="R: CallL2Fam<-,IC-method">
-<param name="keyword" value="R: checkIC,IC,missing-method">
-<param name="keyword" value="R: checkIC,IC,L2ParamFamily-method">
-<param name="keyword" value="R: evalIC,IC,numeric-method">
-<param name="keyword" value="R: evalIC,IC,matrix-method">
-<param name="keyword" value="R: infoPlot,IC-method">
-<param name="keyword" value="R: plot,IC-method">
-<param name="keyword" value="R: show,IC-method">
-<param name="keyword" value=" Influence curve">
-</object>
-
-
-<h2>Influence curve</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of (partial) influence curves.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("IC", ...)</code>.
-More frequently they are created via the generating function
-<code>IC</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>CallL2Fam</code>:</dt><dd>Object of class <code>"call"</code>:
-creates an object of the underlying L2-differentiable
-parametric family. </dd>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>. </dd>
-<dt><code>Curve</code>:</dt><dd>Object of class <code>"EuclRandVarList"</code>.</dd>
-<dt><code>Risks</code>:</dt><dd>Object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </dd>
-<dt><code>Infos</code>:</dt><dd>Object of class <code>"matrix"</code>
-with two columns named <code>method</code> and <code>message</code>:
-additional informations. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"InfluenceCurve"</code>, directly.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>CallL2Fam</dt><dd><code>signature(object = "IC")</code>:
-accessor function for slot <code>CallL2Fam</code>. </dd>
-
-
-<dt>CallL2Fam<-</dt><dd><code>signature(object = "IC")</code>:
-replacement function for slot <code>CallL2Fam</code>. </dd>
-
-
-<dt>checkIC</dt><dd><code>signature(IC = "IC", L2Fam = "missing")</code>:
-check centering and Fisher consistency of <code>IC</code> assuming
-the L2-differentiable parametric family which can
-be generated via the slot <code>CallL2Fam</code> of <code>IC</code>. </dd>
-
-
-<dt>checkIC</dt><dd><code>signature(IC = "IC", L2Fam = "L2ParamFamily")</code>:
-check centering and Fisher consistency of <code>IC</code> assuming
-the L2-differentiable parametric family <code>L2Fam</code>. </dd>
-
-
-<dt>evalIC</dt><dd><code>signature(IC = "IC", x = "numeric")</code>:
-evaluate <code>IC</code> at <code>x</code>. </dd>
-
-
-<dt>evalIC</dt><dd><code>signature(IC = "IC", x = "matrix")</code>:
-evaluate <code>IC</code> at the rows of <code>x</code>. </dd>
-
-
-<dt>infoPlot</dt><dd><code>signature(object = "IC")</code>:
-Plot absolute and relative information of <code>IC</code>. </dd>
-
-
-<dt>plot</dt><dd><code>signature(x = "IC")</code></dd>
-
-
-<dt>show</dt><dd><code>signature(object = "IC")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>, <code><a href="IC.html">IC</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- new("IC")
-plot(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/IC.html
===================================================================
--- pkg/ROptEst/chm/IC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/IC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,115 +0,0 @@
-<html><head><title>Generating function for IC-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>IC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: IC">
-<param name="keyword" value=" Generating function for IC-class">
-</object>
-
-
-<h2>Generating function for IC-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"IC"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-IC(name, Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x}),
- Domain = Reals())),
- Risks, Infos, CallL2Fam = call("L2ParamFamily"))
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-Object of class <code>"character"</code>. </td></tr>
-<tr valign="top"><td><code>CallL2Fam</code></td>
-<td>
-object of class <code>"call"</code>:
-creates an object of the underlying L2-differentiable
-parametric family. </td></tr>
-<tr valign="top"><td><code>Curve</code></td>
-<td>
-object of class <code>"EuclRandVarList"</code>. </td></tr>
-<tr valign="top"><td><code>Risks</code></td>
-<td>
-object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </td></tr>
-<tr valign="top"><td><code>Infos</code></td>
-<td>
-matrix of characters with two columns
-named <code>method</code> and <code>message</code>: additional informations. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"IC"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- IC()
-plot(IC1)
-
-## The function is currently defined as
-IC <- function(name, Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x})),
- Domain = Reals()), Risks, Infos, CallL2Fam = call("L2ParamFamily")){
- if(missing(name))
- name <- "square integrable (partial) influence curve"
- if(missing(Risks))
- Risks <- list()
- if(missing(Infos))
- Infos <- matrix(c(character(0),character(0)), ncol=2,
- dimnames=list(character(0), c("method", "message")))
- return(new("IC", name = name, Curve = Curve, Risks = Risks,
- Infos = Infos, CallL2Fam = CallL2Fam))
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/InfRobModel-class.html
===================================================================
--- pkg/ROptEst/chm/InfRobModel-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/InfRobModel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,95 +0,0 @@
-<html><head><title>Robust model with infinitesimal (unconditional) neighborhood</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>InfRobModel-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: InfRobModel-class">
-<param name="keyword" value="R: neighbor<-,InfRobModel-method">
-<param name="keyword" value="R: show,InfRobModel-method">
-<param name="keyword" value=" Robust model with infinitesimal (unconditional) neighborhood">
-</object>
-
-
-<h2>Robust model with infinitesimal (unconditional) neighborhood</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of robust models with infinitesimal (unconditional) neighborhoods;
-i.e., the neighborhood is shrinking at a rate of <i>sqrt(n)</i>.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("InfRobModel", ...)</code>.
-More frequently they are created via the generating function
-<code>InfRobModel</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>center</code>:</dt><dd>Object of class <code>"ProbFamily"</code>. </dd>
-<dt><code>neighbor</code>:</dt><dd>Object of class <code>"UncondNeighborhood"</code>. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"RobModel"</code>, directly.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>neighbor<-</dt><dd><code>signature(object = "InfRobModel")</code>:
-replacement function for slot <code>neighbor<-</code> </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "InfRobModel")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ProbFamily-class.html">ProbFamily-class</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>,
-<code><a href="InfRobModel.html">InfRobModel</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("InfRobModel")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/InfRobModel.html
===================================================================
--- pkg/ROptEst/chm/InfRobModel.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/InfRobModel.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-<html><head><title>Generating function for InfRobModel-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>InfRobModel(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: InfRobModel">
-<param name="keyword" value=" Generating function for InfRobModel-class">
-</object>
-
-
-<h2>Generating function for InfRobModel-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"InfRobModel"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-InfRobModel(center = L2ParamFamily(), neighbor = ContNeighborhood())
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>center</code></td>
-<td>
-object of class <code>"ProbFamily"</code> </td></tr>
-<tr valign="top"><td><code>neighbor</code></td>
-<td>
-object of class <code>"UncondNeighborhood"</code> </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"FixRobModel"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="RobModel-class.html">RobModel-class</a></code>, <code><a href="FixRobModel-class.html">FixRobModel-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(M1 <- InfRobModel())
-
-## The function is currently defined as
-function(center = L2ParamFamily(), neighbor = ContNeighborhood()){
- new("InfRobModel", center = center, neighbor = neighbor)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/InfluenceCurve-class.html
===================================================================
--- pkg/ROptEst/chm/InfluenceCurve-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/InfluenceCurve-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,157 +0,0 @@
-<html><head><title>Influence curve</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>InfluenceCurve-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: InfluenceCurve-class">
-<param name="keyword" value="R: addInfo<-">
-<param name="keyword" value="R: addInfo<-,InfluenceCurve-method">
-<param name="keyword" value="R: addRisk<-">
-<param name="keyword" value="R: addRisk<-,InfluenceCurve-method">
-<param name="keyword" value="R: Curve">
-<param name="keyword" value="R: Curve,InfluenceCurve-method">
-<param name="keyword" value="R: Domain,InfluenceCurve-method">
-<param name="keyword" value="R: Infos">
-<param name="keyword" value="R: Infos,InfluenceCurve-method">
-<param name="keyword" value="R: Infos<-">
-<param name="keyword" value="R: Infos<-,InfluenceCurve-method">
-<param name="keyword" value="R: Map,InfluenceCurve-method">
-<param name="keyword" value="R: name,InfluenceCurve-method">
-<param name="keyword" value="R: name<-,InfluenceCurve-method">
-<param name="keyword" value="R: Range,InfluenceCurve-method">
-<param name="keyword" value="R: Risks">
-<param name="keyword" value="R: Risks,InfluenceCurve-method">
-<param name="keyword" value="R: Risks<-">
-<param name="keyword" value="R: Risks<-,InfluenceCurve-method">
-<param name="keyword" value="R: show,InfluenceCurve-method">
-<param name="keyword" value=" Influence curve">
-</object>
-
-
-<h2>Influence curve</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of influence curves (functions).
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("InfluenceCurve", ...)</code>.
-More frequently they are created via the generating function
-<code>InfluenceCurve</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>object of class <code>"character"</code> </dd>
-<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code> </dd>
-<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </dd>
-<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
-with two columns named <code>method</code> and <code>message</code>:
-additional informations. </dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>name</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>name</code>. </dd>
-
-
-<dt>name<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-replacement function for slot <code>name</code>. </dd>
-
-
-<dt>Curve</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>Curve</code>. </dd>
-
-
-<dt>Map</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>Map</code> of slot <code>Curve</code>. </dd>
-
-
-<dt>Domain</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>Domain</code> of slot <code>Curve</code>. </dd>
-
-
-<dt>Range</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>Range</code> of slot <code>Curve</code>. </dd>
-
-
-<dt>Infos</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>Infos</code>. </dd>
-
-
-<dt>Infos<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-replacement function for slot <code>Infos</code>. </dd>
-
-
-<dt>addInfo<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-function to add an information to slot <code>Infos</code>. </dd>
-
-
-<dt>Risks</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-accessor function for slot <code>Risks</code>. </dd>
-
-
-<dt>Risks<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-replacement function for slot <code>Risks</code>. </dd>
-
-
-<dt>addRisk<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
-function to add a risk to slot <code>Risks</code>. </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "InfluenceCurve")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="InfluenceCurve.html">InfluenceCurve</a></code>, <code><a href="RiskType-class.html">RiskType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("InfluenceCurve")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/InfluenceCurve.html
===================================================================
--- pkg/ROptEst/chm/InfluenceCurve.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/InfluenceCurve.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,108 +0,0 @@
-<html><head><title>Generating function for InfluenceCurve-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>InfluenceCurve(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: InfluenceCurve">
-<param name="keyword" value=" Generating function for InfluenceCurve-class">
-</object>
-
-
-<h2>Generating function for InfluenceCurve-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"InfluenceCurve"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-InfluenceCurve(name, Curve = EuclRandVarList(EuclRandVariable(Domain = Reals())),
- Risks, Infos)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-character string: name of the influence curve </td></tr>
-<tr valign="top"><td><code>Curve</code></td>
-<td>
-object of class <code>"EuclRandVarList"</code> </td></tr>
-<tr valign="top"><td><code>Risks</code></td>
-<td>
-list of risks </td></tr>
-<tr valign="top"><td><code>Infos</code></td>
-<td>
-matrix of characters with two columns
-named <code>method</code> and <code>message</code>: additional informations </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"InfluenceCurve"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-InfluenceCurve()
-
-## The function is currently defined as
-InfluenceCurve <- function(name, Curve = EuclRandVarList(EuclRandVariable(Domain = Reals())),
- Risks, Infos){
- if(missing(name))
- name <- "influence curve"
- if(missing(Risks))
- Risks <- list()
- if(missing(Infos))
- Infos <- matrix(c(character(0),character(0)), ncol=2,
- dimnames=list(character(0), c("method", "message")))
-
- return(new("InfluenceCurve", name = name, Curve = Curve,
- Risks = Risks, Infos = Infos))
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/L2ParamFamily-class.html
===================================================================
--- pkg/ROptEst/chm/L2ParamFamily-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/L2ParamFamily-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,160 +0,0 @@
-<html><head><title>L2 differentiable parametric family</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>L2ParamFamily-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: L2ParamFamily-class">
-<param name="keyword" value="R: FisherInfo">
-<param name="keyword" value="R: FisherInfo,L2ParamFamily-method">
-<param name="keyword" value="R: L2deriv">
-<param name="keyword" value="R: L2deriv,L2ParamFamily-method">
-<param name="keyword" value="R: L2derivSymm">
-<param name="keyword" value="R: L2derivSymm,L2ParamFamily-method">
-<param name="keyword" value="R: L2derivDistr">
-<param name="keyword" value="R: L2derivDistr,L2ParamFamily-method">
-<param name="keyword" value="R: L2derivDistrSymm">
-<param name="keyword" value="R: L2derivDistrSymm,L2ParamFamily-method">
-<param name="keyword" value="R: checkL2deriv,L2ParamFamily-method">
-<param name="keyword" value="R: E,L2ParamFamily,EuclRandVariable,missing-method">
-<param name="keyword" value="R: E,L2ParamFamily,EuclRandMatrix,missing-method">
-<param name="keyword" value="R: E,L2ParamFamily,EuclRandVarList,missing-method">
-<param name="keyword" value="R: plot,L2ParamFamily-method">
-<param name="keyword" value=" L2 differentiable parametric family">
-</object>
-
-
-<h2>L2 differentiable parametric family</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of L2 differentiable parametric families.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("L2ParamFamily", ...)</code>.
-More frequently they are created via the generating function
-<code>L2ParamFamily</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>object of class <code>"character"</code>:
-name of the family. </dd>
-<dt><code>distribution</code>:</dt><dd>object of class <code>"Distribution"</code>:
-member of the family. </dd>
-<dt><code>distrSymm</code>:</dt><dd>Object of class <code>"DistributionSymmetry"</code>:
-symmetry of <code>distribution</code>. </dd>
-<dt><code>param</code>:</dt><dd>object of class <code>"ParamFamParameter"</code>:
-parameter of the family. </dd>
-<dt><code>props</code>:</dt><dd>object of class <code>"character"</code>:
-properties of the family. </dd>
-<dt><code>L2deriv</code>:</dt><dd>object of class <code>"EuclRandVariable"</code>:
-L2 derivative of the family. </dd>
-<dt><code>L2derivSymm</code>:</dt><dd>object of class <code>"FunSymmList"</code>:
-symmetry of the maps included in <code>L2deriv</code>. </dd>
-<dt><code>L2derivDistr</code>:</dt><dd>object of class <code>"UnivarDistrList"</code>:
-list which includes the distribution of <code>L2deriv</code>. </dd>
-<dt><code>L2derivDistrSymm</code>:</dt><dd>object of class <code>"DistrSymmList"</code>:
-symmetry of the distributions included in <code>L2derivDistr</code>. </dd>
-<dt><code>FisherInfo</code>:</dt><dd>object of class <code>"PosDefSymmMatrix"</code>:
-Fisher information of the family. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"ParamFamily"</code>, directly.<br>
-Class <code>"ProbFamily"</code>, by class <code>"ParamFamily"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>L2deriv</dt><dd><code>signature(object = "L2ParamFamily")</code>:
-accessor function for <code>L2deriv</code>. </dd>
-
-
-<dt>L2derivSymm</dt><dd><code>signature(object = "L2ParamFamily")</code>:
-accessor function for <code>L2derivSymm</code>. </dd>
-
-
-<dt>L2derivDistr</dt><dd><code>signature(object = "L2ParamFamily")</code>:
-accessor function for <code>L2derivDistr</code>. </dd>
-
-
-<dt>L2derivDistrSymm</dt><dd><code>signature(object = "L2ParamFamily")</code>:
-accessor function for <code>L2derivDistrSymm</code>. </dd>
-
-
-<dt>FisherInfo</dt><dd><code>signature(object = "L2ParamFamily")</code>:
-accessor function for <code>FisherInfo</code>. </dd>
-
-
-<dt>checkL2deriv</dt><dd><code>signature(object = "L2ParamFamily")</code>:
-check centering of <code>L2deriv</code> and compute precision
-of Fisher information. </dd>
-
-
-<dt>E</dt><dd><code>signature(object = "L2ParamFamily", fun = "EuclRandVariable", cond = "missing")</code>:
-expectation of <code>fun</code> under the distribution of <code>object</code>. </dd>
-
-
-<dt>E</dt><dd><code>signature(object = "L2ParamFamily", fun = "EuclRandMatrix", cond = "missing")</code>:
-expectation of <code>fun</code> under the distribution of <code>object</code>. </dd>
-
-
-<dt>E</dt><dd><code>signature(object = "L2ParamFamily", fun = "EuclRandVarList", cond = "missing")</code>:
-expectation of <code>fun</code> under the distribution of <code>object</code>. </dd>
-
-
-<dt>plot</dt><dd><code>signature(x = "L2ParamFamily")</code>:
-plot of <code>distribution</code> and <code>L2deriv</code>. </dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily.html">L2ParamFamily</a></code>, <code><a href="ParamFamily-class.html">ParamFamily-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-F1 <- new("L2ParamFamily")
-plot(F1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/L2ParamFamily.html
===================================================================
--- pkg/ROptEst/chm/L2ParamFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/L2ParamFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,146 +0,0 @@
-<html><head><title>Generating function for L2ParamFamily-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>L2ParamFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: L2ParamFamily">
-<param name="keyword" value=" Generating function for L2ParamFamily-class">
-</object>
-
-
-<h2>Generating function for L2ParamFamily-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-L2ParamFamily(name, distribution = Norm(), distrSymm,
- main = 0, nuisance, trafo, param, props = character(0),
- L2deriv = EuclRandVarList(RealRandVariable(list(function(x) {x}),
- Domain = Reals())),
- L2derivSymm, L2derivDistr, L2derivDistrSymm, FisherInfo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-character string: name of the family </td></tr>
-<tr valign="top"><td><code>distribution</code></td>
-<td>
-object of class <code>"Distribution"</code>:
-member of the family </td></tr>
-<tr valign="top"><td><code>distrSymm</code></td>
-<td>
-object of class <code>"DistributionSymmetry"</code>:
-symmetry of <code>distribution</code>. </td></tr>
-<tr valign="top"><td><code>main</code></td>
-<td>
-numeric vector: main parameter </td></tr>
-<tr valign="top"><td><code>nuisance</code></td>
-<td>
-numeric vector: nuisance parameter </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-<tr valign="top"><td><code>param</code></td>
-<td>
-object of class <code>"ParamFamParameter"</code>:
-parameter of the family </td></tr>
-<tr valign="top"><td><code>props</code></td>
-<td>
-character vector: properties of the family </td></tr>
-<tr valign="top"><td><code>L2deriv</code></td>
-<td>
-object of class <code>"EuclRandVariable"</code>:
-L2 derivative of the family </td></tr>
-<tr valign="top"><td><code>L2derivSymm</code></td>
-<td>
-object of class <code>"FunSymmList"</code>:
-symmetry of the maps contained in <code>L2deriv</code> </td></tr>
-<tr valign="top"><td><code>L2derivDistr</code></td>
-<td>
-object of class <code>"UnivarDistrList"</code>:
-distribution of <code>L2deriv</code> </td></tr>
-<tr valign="top"><td><code>L2derivDistrSymm</code></td>
-<td>
-object of class <code>"DistrSymmList"</code>:
-symmetry of the distributions contained in <code>L2derivDistr</code> </td></tr>
-<tr valign="top"><td><code>FisherInfo</code></td>
-<td>
-object of class <code>"PosDefSymmMatrix"</code>:
-Fisher information of the family </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-If <code>name</code> is missing, the default
-“L2 differentiable parametric family of probability measures”
-is used. In case <code>distrSymm</code> is missing it is set to
-<code>NoSymmetry()</code>.
-If <code>param</code> is missing, the parameter is created via
-<code>main</code>, <code>nuisance</code> and <code>trafo</code> as described
-in <code><a href="ParamFamParameter.html">ParamFamParameter</a></code>. In case <code>L2derivSymm</code> is
-missing, it is filled with an object of class <code>FunSymmList</code>
-with entries <code>NonSymmetric()</code>. In case <code>L2derivDistr</code> is missing,
-it is computed via <code>imageDistr</code>. If <code>L2derivDistrSymm</code> is missing,
-it is set to an object of class <code>DistrSymmList</code> with entries
-<code>NoSymmetry()</code>. In case <code>FisherInfo</code> is missing, it is computed
-from <code>L2deriv</code> using <code>E</code>.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-F1 <- L2ParamFamily()
-plot(F1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/LnormScaleFamily.html
===================================================================
--- pkg/ROptEst/chm/LnormScaleFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/LnormScaleFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,102 +0,0 @@
-<html><head><title>Generating function for lognormal scale families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>LnormScaleFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: LnormScaleFamily">
-<param name="keyword" value=" Generating function for lognormal scale families">
-</object>
-
-
-<h2>Generating function for lognormal scale families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a lognormal scale family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-LnormScaleFamily(meanlog = 0, sdlog = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>meanlog</code></td>
-<td>
-mean of the distribution on the log scale </td></tr>
-<tr valign="top"><td><code>sdlog</code></td>
-<td>
-standard deviation of the distribution on the log scale </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Lnorm-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Lnorm-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(L1 <- LnormScaleFamily())
-plot(L1)
-Map(L2deriv(L1)[[1]])
-checkL2deriv(L1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/Neighborhood-class.html
===================================================================
--- pkg/ROptEst/chm/Neighborhood-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/Neighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,81 +0,0 @@
-<html><head><title>Neighborhood</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>Neighborhood-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: Neighborhood-class">
-<param name="keyword" value="R: radius">
-<param name="keyword" value="R: radius,Neighborhood-method">
-<param name="keyword" value="R: show,Neighborhood-method">
-<param name="keyword" value="R: type,Neighborhood-method">
-<param name="keyword" value=" Neighborhood">
-</object>
-
-
-<h2>Neighborhood</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of neighborhoods of families of probability measures.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-type of the neighborhood. </dd>
-<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
-neighborhood radius. </dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>type</dt><dd><code>signature(object = "Neighborhood")</code>:
-accessor function for slot <code>type</code>. </dd>
-<dt>radius</dt><dd><code>signature(object = "Neighborhood")</code>:
-accessor function for slot <code>radius</code>. </dd>
-<dt>show</dt><dd><code>signature(object = "Neighborhood")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ProbFamily-class.html">ProbFamily-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NoSymmetry-class.html
===================================================================
--- pkg/ROptEst/chm/NoSymmetry-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NoSymmetry-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,81 +0,0 @@
-<html><head><title>Class for Non-symmetric Distributions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NoSymmetry-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NoSymmetry-class">
-<param name="keyword" value=" Class for Non-symmetric Distributions">
-</object>
-
-
-<h2>Class for Non-symmetric Distributions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class for non-symmetric distributions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("NoSymmetry")</code>.
-More frequently they are created via the generating function
-<code>NoSymmetry</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-contains “non-symmetric distribution” </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"NULL"</code> </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"DistributionSymmetry"</code>, directly.<br>
-Class <code>"Symmetry"</code>, by class <code>"DistributionSymmetry"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="NoSymmetry.html">NoSymmetry</a></code>, <code><a onclick="findlink('distr', 'Distribution-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Distribution-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("NoSymmetry")
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NoSymmetry.html
===================================================================
--- pkg/ROptEst/chm/NoSymmetry.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NoSymmetry.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,60 +0,0 @@
-<html><head><title>Generating function for NoSymmetry-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NoSymmetry(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NoSymmetry">
-<param name="keyword" value=" Generating function for NoSymmetry-class">
-</object>
-
-
-<h2>Generating function for NoSymmetry-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"NoSymmetry"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>NoSymmetry()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"NoSymmetry"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="NoSymmetry-class.html">NoSymmetry-class</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-NoSymmetry()
-
-## The function is currently defined as
-function(){ new("NoSymmetry") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NonSymmetric-class.html
===================================================================
--- pkg/ROptEst/chm/NonSymmetric-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NonSymmetric-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,72 +0,0 @@
-<html><head><title>Class for Non-symmetric Functions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NonSymmetric-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NonSymmetric-class">
-<param name="keyword" value=" Class for Non-symmetric Functions">
-</object>
-
-
-<h2>Class for Non-symmetric Functions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class for non-symmetric functions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("NonSymmetric")</code>.
-More frequently they are created via the generating function
-<code>NonSymmetric</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-contains “non-symmetric function” </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"NULL"</code> </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"FunctionSymmetry"</code>, directly.<br>
-Class <code>"Symmetry"</code>, by class <code>"FunctionSymmetry"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="NonSymmetric.html">NonSymmetric</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("NonSymmetric")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NonSymmetric.html
===================================================================
--- pkg/ROptEst/chm/NonSymmetric.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NonSymmetric.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,60 +0,0 @@
-<html><head><title>Generating function for NonSymmetric-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NonSymmetric(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NonSymmetric">
-<param name="keyword" value=" Generating function for NonSymmetric-class">
-</object>
-
-
-<h2>Generating function for NonSymmetric-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"NonSymmetric"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>NonSymmetric()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"NonSymmetric"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="NonSymmetric-class.html">NonSymmetric-class</a></code>, <code><a href="FunctionSymmetry-class.html">FunctionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-NonSymmetric()
-
-## The function is currently defined as
-function(){ new("NonSymmetric") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NormLocationFamily.html
===================================================================
--- pkg/ROptEst/chm/NormLocationFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NormLocationFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,101 +0,0 @@
-<html><head><title>Generating function for normal location families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NormLocationFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NormLocationFamily">
-<param name="keyword" value=" Generating function for normal location families">
-</object>
-
-
-<h2>Generating function for normal location families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a normal location family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-NormLocationFamily(mean = 0, sd = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>mean</code></td>
-<td>
-mean </td></tr>
-<tr valign="top"><td><code>sd</code></td>
-<td>
-standard deviation </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Norm-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Norm-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(N1 <- NormLocationFamily())
-plot(N1)
-L2derivDistr(N1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NormLocationScaleFamily.html
===================================================================
--- pkg/ROptEst/chm/NormLocationScaleFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NormLocationScaleFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,102 +0,0 @@
-<html><head><title>Generating function for normal location and scale families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NormLocationScaleFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NormLocationScaleFamily">
-<param name="keyword" value=" Generating function for normal location and scale families">
-</object>
-
-
-<h2>Generating function for normal location and scale families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a normal location and scale family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-NormLocationScaleFamily(mean = 0, sd = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>mean</code></td>
-<td>
-mean </td></tr>
-<tr valign="top"><td><code>sd</code></td>
-<td>
-standard deviation </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Norm-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Norm-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(N1 <- NormLocationScaleFamily())
-plot(N1)
-FisherInfo(N1)
-checkL2deriv(N1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/NormScaleFamily.html
===================================================================
--- pkg/ROptEst/chm/NormScaleFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/NormScaleFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,102 +0,0 @@
-<html><head><title>Generating function for normal scale families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>NormScaleFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: NormScaleFamily">
-<param name="keyword" value=" Generating function for normal scale families">
-</object>
-
-
-<h2>Generating function for normal scale families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a normal scale family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-NormScaleFamily(sd = 1, mean = 0, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>sd</code></td>
-<td>
-standard deviation </td></tr>
-<tr valign="top"><td><code>mean</code></td>
-<td>
-mean </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Norm-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Norm-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(N1 <- NormScaleFamily())
-plot(N1)
-FisherInfo(N1)
-checkL2deriv(N1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/OddSymmetric-class.html
===================================================================
--- pkg/ROptEst/chm/OddSymmetric-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/OddSymmetric-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,73 +0,0 @@
-<html><head><title>Class for Odd Functions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>OddSymmetric-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: OddSymmetric-class">
-<param name="keyword" value=" Class for Odd Functions">
-</object>
-
-
-<h2>Class for Odd Functions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class for odd functions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("OddSymmetric")</code>.
-More frequently they are created via the generating function
-<code>OddSymmetric</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-contains “odd function” </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"numeric"</code>:
-center of symmetry </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"FunctionSymmetry"</code>, directly.<br>
-Class <code>"Symmetry"</code>, by class <code>"FunctionSymmetry"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="OddSymmetric.html">OddSymmetric</a></code>, <code><a href="FunctionSymmetry-class.html">FunctionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("OddSymmetric")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/OddSymmetric.html
===================================================================
--- pkg/ROptEst/chm/OddSymmetric.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/OddSymmetric.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,70 +0,0 @@
-<html><head><title>Generating function for OddSymmetric-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>OddSymmetric(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: OddSymmetric">
-<param name="keyword" value=" Generating function for OddSymmetric-class">
-</object>
-
-
-<h2>Generating function for OddSymmetric-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"OddSymmetric"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>OddSymmetric(SymmCenter = 0)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>SymmCenter</code></td>
-<td>
-numeric: center of symmetry </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"OddSymmetric"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="OddSymmetric-class.html">OddSymmetric-class</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-OddSymmetric()
-
-## The function is currently defined as
-function(SymmCenter = 0){
- new("OddSymmetric", SymmCenter = SymmCenter)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/OptionalNumeric-class.html
===================================================================
--- pkg/ROptEst/chm/OptionalNumeric-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/OptionalNumeric-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,56 +0,0 @@
-<html><head><title>Optional numeric</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>OptionalNumeric-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: OptionalNumeric-class">
-<param name="keyword" value=" Optional numeric">
-</object>
-
-
-<h2>Optional numeric</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Optional object of class <code>"numeric"</code>.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a onclick="findlink('methods', 'BasicClasses.html')" style="text-decoration: underline; color: blue; cursor: hand">numeric-class</a></code>
-</p>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ParamFamParameter-class.html
===================================================================
--- pkg/ROptEst/chm/ParamFamParameter-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ParamFamParameter-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,134 +0,0 @@
-<html><head><title>Parameter of a parametric family of probability measures</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ParamFamParameter-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ParamFamParameter-class">
-<param name="keyword" value="R: length,ParamFamParameter-method">
-<param name="keyword" value="R: main">
-<param name="keyword" value="R: main,ParamFamParameter-method">
-<param name="keyword" value="R: main<-">
-<param name="keyword" value="R: main<-,ParamFamParameter-method">
-<param name="keyword" value="R: nuisance">
-<param name="keyword" value="R: nuisance,ParamFamParameter-method">
-<param name="keyword" value="R: nuisance<-">
-<param name="keyword" value="R: nuisance<-,ParamFamParameter-method">
-<param name="keyword" value="R: show,ParamFamParameter-method">
-<param name="keyword" value="R: trafo">
-<param name="keyword" value="R: trafo,ParamFamParameter-method">
-<param name="keyword" value="R: trafo<-">
-<param name="keyword" value="R: trafo<-,ParamFamParameter-method">
-<param name="keyword" value=" Parameter of a parametric family of probability measures">
-</object>
-
-
-<h2>Parameter of a parametric family of probability measures</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of the parameter of parametric families
-of probability measures.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("ParamFamParameter", ...)</code>.
-More frequently they are created via the generating function
-<code>ParamFamParameter</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>main</code>:</dt><dd>Object of class <code>"numeric"</code>: main parameter. </dd>
-<dt><code>nuisance</code>:</dt><dd>Object of class <code>"OptionalNumeric"</code>:
-optional nuisance parameter. </dd>
-<dt><code>trafo</code>:</dt><dd>Object of class <code>"matrix"</code>:
-transformation of the parameter. </dd>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>:
-name of the parameter. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"Parameter"</code>, directly.<br>
-Class <code>"OptionalParameter"</code>, by class <code>"Parameter"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>main</dt><dd><code>signature(object = "ParamFamParameter")</code>:
-accessor function for slot <code>main</code>. </dd>
-
-
-<dt>main<-</dt><dd><code>signature(object = "ParamFamParameter")</code>:
-replacement function for slot <code>main</code>. </dd>
-
-
-<dt>nuisance</dt><dd><code>signature(object = "ParamFamParameter")</code>:
-accessor function for slot <code>nuisance</code>. </dd>
-
-
-<dt>nuisance<-</dt><dd><code>signature(object = "ParamFamParameter")</code>:
-replacement function for slot <code>nuisance</code>. </dd>
-
-
-<dt>trafo</dt><dd><code>signature(object = "ParamFamParameter")</code>:
-accessor function for slot <code>trafo</code>. </dd>
-
-
-<dt>trafo<-</dt><dd><code>signature(object = "ParamFamParameter")</code>:
-replacement function for slot <code>trafo</code>. </dd>
-
-
-<dt>length</dt><dd><code>signature(x = "ParamFamParameter")</code>:
-sum of the lengths of <code>main</code> and <code>nuisance</code>. </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "ParamFamParameter")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a onclick="findlink('distr', 'Parameter-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Parameter-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("ParamFamParameter")
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ParamFamParameter.html
===================================================================
--- pkg/ROptEst/chm/ParamFamParameter.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ParamFamParameter.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,103 +0,0 @@
-<html><head><title>Generating function for ParamFamParameter-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ParamFamParameter(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ParamFamParameter">
-<param name="keyword" value=" Generating function for ParamFamParameter-class">
-</object>
-
-
-<h2>Generating function for ParamFamParameter-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"ParamFamParameter"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-ParamFamParameter(name, main = numeric(0), nuisance, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-character string: name of parameter </td></tr>
-<tr valign="top"><td><code>main</code></td>
-<td>
-numeric vector: main parameter </td></tr>
-<tr valign="top"><td><code>nuisance</code></td>
-<td>
-numeric vector: nuisance paramter </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-If <code>name</code> is missing, the default
-“"parameter of a parametric family of probability measures"”
-is used. If <code>nuisance</code> is missing, the nuisance parameter is
-set to <code>NULL</code>. The number of columns of <code>trafo</code> have
-to be equal and the number of rows have to be not larger than
-the sum of the lengths of <code>main</code> and <code>nuisance</code>.
-If <code>trafo</code> is missing, no transformation to the parameter
-is applied; i.e., <code>trafo</code> is set to an identity matrix.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"ParamFamParameter"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ParamFamParameter-class.html">ParamFamParameter-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-ParamFamParameter(main = 0, nuisance = 1, trafo = diag(c(1,2)))
-
-## The function is currently defined as
-function(name, main = numeric(0), nuisance, trafo){
- if(missing(name))
- name <- "parameter of a parametric family of probability measures"
- if(missing(nuisance))
- nuisance <- NULL
- if(missing(trafo))
- trafo <- diag(length(main)+length(nuisance))
-
- return(new("ParamFamParameter", name = name, main = main,
- nuisance = nuisance, trafo = trafo))
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ParamFamily-class.html
===================================================================
--- pkg/ROptEst/chm/ParamFamily-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ParamFamily-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,123 +0,0 @@
-<html><head><title>Parametric family of probability measures.</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ParamFamily-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ParamFamily-class">
-<param name="keyword" value="R: main,ParamFamily-method">
-<param name="keyword" value="R: nuisance,ParamFamily-method">
-<param name="keyword" value="R: param,ParamFamily-method">
-<param name="keyword" value="R: plot,ParamFamily-method">
-<param name="keyword" value="R: show,ParamFamily-method">
-<param name="keyword" value="R: trafo,ParamFamily-method">
-<param name="keyword" value=" Parametric family of probability measures.">
-</object>
-
-
-<h2>Parametric family of probability measures.</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of parametric families of probability measures.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("ParamFamily", ...)</code>.
-More frequently they are created via the generating function
-<code>ParamFamily</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>param</code>:</dt><dd>Object of class <code>"ParamFamParameter"</code>:
-parameter of the family. </dd>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>:
-name of the family. </dd>
-<dt><code>distribution</code>:</dt><dd>Object of class <code>"Distribution"</code>:
-member of the family.</dd>
-<dt><code>distrSymm</code>:</dt><dd>Object of class <code>"DistributionSymmetry"</code>:
-symmetry of <code>distribution</code>. </dd>
-<dt><code>props</code>:</dt><dd>Object of class <code>"character"</code>:
-properties of the family. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"ProbFamily"</code>, directly.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>main</dt><dd><code>signature(object = "ParamFamily")</code>:
-wrapped accessor function for slot <code>main</code> of
-slot <code>param</code>. </dd>
-
-
-<dt>nuisance</dt><dd><code>signature(object = "ParamFamily")</code>:
-wrapped accessor function for slot <code>nuisance</code>
-of slot <code>param</code>. </dd>
-
-
-<dt>trafo</dt><dd><code>signature(object = "ParamFamily")</code>:
-wrapped accessor function for slot <code>trafo</code>
-of slot <code>param</code>. </dd>
-
-
-<dt>param</dt><dd><code>signature(object = "ParamFamily")</code>:
-accessor function for slot <code>param</code>. </dd>
-
-
-<dt>plot</dt><dd><code>signature(x = "ParamFamily")</code>:
-plot of slot <code>distribution</code>. </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "ParamFamily")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a onclick="findlink('distr', 'Distribution-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Distribution-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-F1 <- new("ParamFamily") # prototype
-plot(F1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ParamFamily.html
===================================================================
--- pkg/ROptEst/chm/ParamFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ParamFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,119 +0,0 @@
-<html><head><title>Generating function for ParamFamily-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ParamFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ParamFamily">
-<param name="keyword" value=" Generating function for ParamFamily-class">
-</object>
-
-
-<h2>Generating function for ParamFamily-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"ParamFamily"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-ParamFamily(name, distribution = Norm(), distrSymm, main = 0,
- nuisance, trafo, param, props = character(0))
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-character string: name of family </td></tr>
-<tr valign="top"><td><code>distribution</code></td>
-<td>
-object of class <code>"Distribution"</code>:
-member of the family </td></tr>
-<tr valign="top"><td><code>distrSymm</code></td>
-<td>
-object of class <code>"DistributionSymmetry"</code>:
-symmetry of <code>distribution</code>. </td></tr>
-<tr valign="top"><td><code>main</code></td>
-<td>
-numeric vector: main parameter </td></tr>
-<tr valign="top"><td><code>nuisance</code></td>
-<td>
-numeric vector: nuisance parameter </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameters </td></tr>
-<tr valign="top"><td><code>param</code></td>
-<td>
-object of class <code>"ParamFamParameter"</code>:
-parameter of the family </td></tr>
-<tr valign="top"><td><code>props</code></td>
-<td>
-character vector: properties of the family </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-If <code>name</code> is missing, the default
-“"parametric family of probability measures"” is used.
-In case <code>distrSymm</code> is missing it is set
-to <code>NoSymmetry()</code>.
-If <code>param</code> is missing, the parameter is created via
-<code>main</code>, <code>nuisance</code> and <code>trafo</code> as described
-in <code><a href="ParamFamParameter.html">ParamFamParameter</a></code>.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ParamFamily-class.html">ParamFamily-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-F1 <- ParamFamily()
-plot(F1)
-
-## The function is currently defined as
-function(name, distribution = Norm(), main = 0, nuisance,
- trafo, param, props = character(0)){
- if(missing(name))
- name <- "parametric family of probability measures"
- if(missing(distrSymm)) distrSymm <- NoSymmetry()
- if(missing(param))
- param <- ParamFamParameter(name = paste("parameter of", name),
- main = main, nuisance = nuisance, trafo = trafo)
- return(new("ParamFamily", name = name, distribution = distribution,
- distrSymm = distrSymm, param = param, props = props))
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/PoisFamily.html
===================================================================
--- pkg/ROptEst/chm/PoisFamily.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/PoisFamily.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,99 +0,0 @@
-<html><head><title>Generating function for Poisson families</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>PoisFamily(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: PoisFamily">
-<param name="keyword" value=" Generating function for Poisson families">
-</object>
-
-
-<h2>Generating function for Poisson families</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"L2ParamFamily"</code> which
-represents a Poisson family.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-PoisFamily(lambda = 1, trafo)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>lambda</code></td>
-<td>
-positive mean </td></tr>
-<tr valign="top"><td><code>trafo</code></td>
-<td>
-matrix: transformation of the parameter </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The slots of the corresponding L2 differentiable
-parameteric family are filled.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"L2ParamFamily"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to
-the Asymptotic Theory of Robustness</EM>. Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a onclick="findlink('distr', 'Pois-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Pois-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-(P1 <- PoisFamily(lambda = 4.5))
-plot(P1)
-FisherInfo(P1)
-checkL2deriv(P1)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/PosDefSymmMatrix-class.html
===================================================================
--- pkg/ROptEst/chm/PosDefSymmMatrix-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/PosDefSymmMatrix-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Positive-definite, symmetric matrices</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>PosDefSymmMatrix-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: PosDefSymmMatrix-class">
-<param name="keyword" value=" Positive-definite symmetric matrices">
-</object>
-
-
-<h2>Positive-definite symmetric matrices</h2>
-
-
-<h3>Description</h3>
-
-<p>
-The class of positive-definite, symmetric matrices.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("PosDefSymmMatrix", ...)</code>.
-More frequently they are created via the generating function
-<code>PosDefSymmMatrix</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>.Data</code>:</dt><dd>Object of class <code>"matrix"</code>.
-A numeric matrix with finite entries.</dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"matrix"</code>, from data part.<br>
-Class <code>"structure"</code>, by class <code>"matrix"</code>.<br>
-Class <code>"array"</code>, by class <code>"matrix"</code>.<br>
-Class <code>"vector"</code>, by class "matrix", with explicit coerce.<br>
-Class <code>"vector"</code>, by class "matrix", with explicit coerce.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="PosDefSymmMatrix.html">PosDefSymmMatrix</a></code>, <code><a onclick="findlink('methods', 'StructureClasses.html')" style="text-decoration: underline; color: blue; cursor: hand">matrix-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("PosDefSymmMatrix", diag(2))
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/PosDefSymmMatrix.html
===================================================================
--- pkg/ROptEst/chm/PosDefSymmMatrix.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/PosDefSymmMatrix.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,80 +0,0 @@
-<html><head><title>Generating function for PosDefSymmMatrix-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>PosDefSymmMatrix(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: PosDefSymmMatrix">
-<param name="keyword" value=" Generating function for PosDefSymmMatrix-class">
-</object>
-
-
-<h2>Generating function for PosDefSymmMatrix-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"PosDefSymmMatrix"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>PosDefSymmMatrix(mat)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>mat</code></td>
-<td>
-A numeric positive-definite, symmetric
-matrix with finite entries.</td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-If <code>mat</code> is no matrix, <code>as.matrix</code> is applied.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"PosDefSymmMatrix"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="PosDefSymmMatrix-class.html">PosDefSymmMatrix-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-PosDefSymmMatrix(1)
-PosDefSymmMatrix(diag(2))
-
-## The function is currently defined as
-function(mat){
- if(!is.matrix(mat)) mat <- as.matrix(mat)
- new("PosDefSymmMatrix", mat)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ProbFamily-class.html
===================================================================
--- pkg/ROptEst/chm/ProbFamily-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ProbFamily-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,112 +0,0 @@
-<html><head><title>Family of probability measures</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ProbFamily-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ProbFamily-class">
-<param name="keyword" value="R: addProp<-">
-<param name="keyword" value="R: addProp<-,ProbFamily-method">
-<param name="keyword" value="R: distribution">
-<param name="keyword" value="R: distribution,ProbFamily-method">
-<param name="keyword" value="R: distrSymm">
-<param name="keyword" value="R: distrSymm,ProbFamily-method">
-<param name="keyword" value="R: name,ProbFamily-method">
-<param name="keyword" value="R: name<-,ProbFamily-method">
-<param name="keyword" value="R: props">
-<param name="keyword" value="R: props,ProbFamily-method">
-<param name="keyword" value="R: props<-">
-<param name="keyword" value="R: props<-,ProbFamily-method">
-<param name="keyword" value=" Family of probability measures">
-</object>
-
-
-<h2>Family of probability measures</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of families of probability measures.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>:
-name of the family. </dd>
-<dt><code>distribution</code>:</dt><dd>Object of class <code>"Distribution"</code>:
-member of the family. </dd>
-<dt><code>distrSymm</code>:</dt><dd>Object of class <code>"DistributionSymmetry"</code>:
-symmetry of <code>distribution</code>. </dd>
-<dt><code>props</code>:</dt><dd>Object of class <code>"character"</code>:
-properties of the family. </dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>name</dt><dd><code>signature(object = "ProbFamily")</code>:
-accessor function for slot <code>name</code>. </dd>
-
-
-<dt>name<-</dt><dd><code>signature(object = "ProbFamily")</code>:
-replacement function for slot <code>name</code>. </dd>
-
-
-<dt>distribution</dt><dd><code>signature(object = "ProbFamily")</code>:
-accessor function for slot <code>distribution</code>. </dd>
-
-
-<dt>distrSymm</dt><dd><code>signature(object = "ProbFamily")</code>:
-accessor function for slot <code>distrSymm</code>. </dd>
-
-
-<dt>props</dt><dd><code>signature(object = "ProbFamily")</code>:
-accessor function for slot <code>props</code>. </dd>
-
-
-<dt>props<-</dt><dd><code>signature(object = "ProbFamily")</code>:
-replacement function for slot <code>props</code>. </dd>
-
-
-<dt>addProp<-</dt><dd><code>signature(object = "ProbFamily")</code>:
-add a property to slot <code>props</code>. </dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a onclick="findlink('distr', 'Distribution-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Distribution-class</a></code>
-</p>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/ROptEst.chm
===================================================================
(Binary files differ)
Modified: pkg/ROptEst/chm/ROptEst.hhp
===================================================================
--- pkg/ROptEst/chm/ROptEst.hhp 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ROptEst.hhp 2008-02-16 03:32:41 UTC (rev 25)
@@ -12,95 +12,8 @@
[FILES]
00Index.html
-BiasType-class.html
-BinomFamily.html
-ContIC-class.html
-ContIC.html
-ContNeighborhood-class.html
-ContNeighborhood.html
-DistrSymmList-class.html
-DistrSymmList.html
-DistributionSymmetry-class.html
-EllipticalSymmetry-class.html
-EllipticalSymmetry.html
-EvenSymmetric-class.html
-EvenSymmetric.html
-ExpScaleFamily.html
-FixRobModel-class.html
-FixRobModel.html
-FunSymmList-class.html
-FunSymmList.html
-FunctionSymmetry-class.html
-GammaFamily.html
-GumbelLocationFamily.html
-IC-class.html
-IC.html
-InfRobModel-class.html
-InfRobModel.html
-InfluenceCurve-class.html
-InfluenceCurve.html
-L2ParamFamily-class.html
-L2ParamFamily.html
-LnormScaleFamily.html
-Neighborhood-class.html
-NoSymmetry-class.html
-NoSymmetry.html
-NonSymmetric-class.html
-NonSymmetric.html
-NormLocationFamily.html
-NormLocationScaleFamily.html
-NormScaleFamily.html
-OddSymmetric-class.html
-OddSymmetric.html
-OptionalNumeric-class.html
-ParamFamParameter-class.html
-ParamFamParameter.html
-ParamFamily-class.html
-ParamFamily.html
-PoisFamily.html
-PosDefSymmMatrix-class.html
-PosDefSymmMatrix.html
-ProbFamily-class.html
-RiskType-class.html
-RobModel-class.html
-SphericalSymmetry-class.html
-SphericalSymmetry.html
-Symmetry-class.html
-TotalVarIC-class.html
-TotalVarIC.html
-TotalVarNeighborhood-class.html
-TotalVarNeighborhood.html
-UncondNeighborhood-class.html
-asBias-class.html
-asBias.html
-asCov-class.html
-asCov.html
-asGRisk-class.html
-asHampel-class.html
-asHampel.html
-asMSE-class.html
-asMSE.html
-asRisk-class.html
-asUnOvShoot-class.html
-asUnOvShoot.html
-asymmetricBias.html
-asymmetricBiasType-class.html
-checkIC.html
-checkL2deriv.html
-evalIC.html
-fiBias-class.html
-fiBias.html
-fiCov-class.html
-fiCov.html
-fiHampel-class.html
-fiHampel.html
-fiMSE-class.html
-fiMSE.html
-fiRisk-class.html
-fiUnOvShoot-class.html
-fiUnOvShoot.html
-generateIC.html
getAsRisk.html
+getBiasIC.html
getFiRisk.html
getFixClip.html
getFixRobIC.html
@@ -110,22 +23,15 @@
getInfGamma.html
getInfRobIC.html
getInfStand.html
+getL1normL2deriv.html
+getL2normL2deriv.html
getRiskIC.html
-infoPlot.html
-ksEstimator.html
leastFavorableRadius.html
locMEstimator.html
lowerCaseRadius.html
-negativeBias.html
-oneStepEstimator.html
-onesidedBiasType-class.html
+minmaxBias.html
optIC.html
optRisk.html
-positiveBias.html
radiusMinimaxIC.html
-symmetricBias.html
-symmetricBiasType-class.html
trAsCov-class.html
-trAsCov.html
trFiCov-class.html
-trFiCov.html
Modified: pkg/ROptEst/chm/ROptEst.toc
===================================================================
--- pkg/ROptEst/chm/ROptEst.toc 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ROptEst.toc 2008-02-16 03:32:41 UTC (rev 25)
@@ -10,468 +10,84 @@
</OBJECT>
<UL>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="addInfo<-">
-<param name="Local" value="InfluenceCurve-class.html">
+<param name="Name" value="getAsRisk">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="addInfo<-,InfluenceCurve-method">
-<param name="Local" value="InfluenceCurve-class.html">
+<param name="Name" value="getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="addProp<-">
-<param name="Local" value="ProbFamily-class.html">
+<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="addProp<-,ProbFamily-method">
-<param name="Local" value="ProbFamily-class.html">
+<param name="Name" value="getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="addRisk<-">
-<param name="Local" value="InfluenceCurve-class.html">
+<param name="Name" value="getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="addRisk<-,InfluenceCurve-method">
-<param name="Local" value="InfluenceCurve-class.html">
+<param name="Name" value="getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asBias">
-<param name="Local" value="asBias.html">
+<param name="Name" value="getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="Local" value="getAsRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asBias-class">
-<param name="Local" value="asBias-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asCov">
-<param name="Local" value="asCov.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asCov-class">
-<param name="Local" value="asCov-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asGRisk-class">
-<param name="Local" value="asGRisk-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asHampel">
-<param name="Local" value="asHampel.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asHampel-class">
-<param name="Local" value="asHampel-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asMSE">
-<param name="Local" value="asMSE.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asMSE-class">
-<param name="Local" value="asMSE-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asRisk-class">
-<param name="Local" value="asRisk-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asUnOvShoot">
-<param name="Local" value="asUnOvShoot.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asUnOvShoot-class">
-<param name="Local" value="asUnOvShoot-class.html">
-</OBJECT>
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-<param name="Name" value="ProbFamily-class">
-<param name="Local" value="ProbFamily-class.html">
-</OBJECT>
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-<param name="Name" value="props">
-<param name="Local" value="ProbFamily-class.html">
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-<param name="Name" value="props,ProbFamily-method">
-<param name="Local" value="ProbFamily-class.html">
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-<param name="Name" value="props<-">
-<param name="Local" value="ProbFamily-class.html">
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-<param name="Name" value="props<-,ProbFamily-method">
-<param name="Local" value="ProbFamily-class.html">
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-<param name="Name" value="radius">
-<param name="Local" value="Neighborhood-class.html">
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-<param name="Name" value="radius,Neighborhood-method">
-<param name="Local" value="Neighborhood-class.html">
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<param name="Name" value="radiusMinimaxIC">
<param name="Local" value="radiusMinimaxIC.html">
</OBJECT>
@@ -1274,539 +502,31 @@
<param name="Local" value="radiusMinimaxIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Range,InfluenceCurve-method">
-<param name="Local" value="InfluenceCurve-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Risks">
-<param name="Local" value="InfluenceCurve-class.html">
-</OBJECT>
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-<param name="Name" value="Risks,InfluenceCurve-method">
-<param name="Local" value="InfluenceCurve-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Risks<-">
-<param name="Local" value="InfluenceCurve-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Risks<-,InfluenceCurve-method">
-<param name="Local" value="InfluenceCurve-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="RiskType-class">
-<param name="Local" value="RiskType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="RobModel-class">
-<param name="Local" value="RobModel-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,asHampel-method">
-<param name="Local" value="asHampel-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,asUnOvShoot-method">
-<param name="Local" value="asUnOvShoot-class.html">
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-<param name="Name" value="show,ContIC-method">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,fiHampel-method">
-<param name="Local" value="fiHampel-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,fiUnOvShoot-method">
-<param name="Local" value="fiUnOvShoot-class.html">
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-<param name="Name" value="show,FixRobModel-method">
-<param name="Local" value="FixRobModel-class.html">
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-<param name="Name" value="show,IC-method">
-<param name="Local" value="IC-class.html">
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-<param name="Name" value="show,InfluenceCurve-method">
-<param name="Local" value="InfluenceCurve-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,InfRobModel-method">
-<param name="Local" value="InfRobModel-class.html">
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-<param name="Name" value="show,Neighborhood-method">
-<param name="Local" value="Neighborhood-class.html">
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-<param name="Name" value="show,ParamFamily-method">
-<param name="Local" value="ParamFamily-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,ParamFamParameter-method">
-<param name="Local" value="ParamFamParameter-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,RiskType-method">
-<param name="Local" value="RiskType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,Symmetry-method">
-<param name="Local" value="Symmetry-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="show,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="sign">
-<param name="Local" value="onesidedBiasType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="sign,onesidedBiasType-method">
-<param name="Local" value="onesidedBiasType-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="sign<-">
-<param name="Local" value="onesidedBiasType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="sign<-,onesidedBiasType-method">
-<param name="Local" value="onesidedBiasType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="SphericalSymmetry">
-<param name="Local" value="SphericalSymmetry.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="SphericalSymmetry-class">
-<param name="Local" value="SphericalSymmetry-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand,ContIC-method">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand<-">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand<-,ContIC-method">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="stand<-,TotalVarIC-method">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="SymmCenter">
-<param name="Local" value="Symmetry-class.html">
-</OBJECT>
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-<param name="Name" value="SymmCenter,Symmetry-method">
-<param name="Local" value="Symmetry-class.html">
-</OBJECT>
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-<param name="Name" value="symmetricBias">
-<param name="Local" value="symmetricBias.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="symmetricBiasType-class">
-<param name="Local" value="symmetricBiasType-class.html">
-</OBJECT>
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-<param name="Name" value="Symmetry-class">
-<param name="Local" value="Symmetry-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="TotalVarIC">
-<param name="Local" value="TotalVarIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="TotalVarIC-class">
-<param name="Local" value="TotalVarIC-class.html">
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-<param name="Name" value="TotalVarNeighborhood">
-<param name="Local" value="TotalVarNeighborhood.html">
-</OBJECT>
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-<param name="Name" value="TotalVarNeighborhood-class">
-<param name="Local" value="TotalVarNeighborhood-class.html">
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-<param name="Name" value="trafo">
-<param name="Local" value="ParamFamParameter-class.html">
-</OBJECT>
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-<param name="Name" value="trafo,ParamFamily-method">
-<param name="Local" value="ParamFamily-class.html">
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-<param name="Name" value="trafo,ParamFamParameter-method">
-<param name="Local" value="ParamFamParameter-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="trafo<-">
-<param name="Local" value="ParamFamParameter-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="trafo<-,ParamFamParameter-method">
-<param name="Local" value="ParamFamParameter-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="trAsCov">
-<param name="Local" value="trAsCov.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="trAsCov-class">
<param name="Local" value="trAsCov-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="trFiCov">
-<param name="Local" value="trFiCov.html">
-</OBJECT>
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<param name="Name" value="trFiCov-class">
<param name="Local" value="trFiCov-class.html">
</OBJECT>
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-<param name="Name" value="type">
-<param name="Local" value="Symmetry-class.html">
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-<param name="Name" value="type,Neighborhood-method">
-<param name="Local" value="Neighborhood-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="type,RiskType-method">
-<param name="Local" value="RiskType-class.html">
-</OBJECT>
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-<param name="Name" value="type,Symmetry-method">
-<param name="Local" value="Symmetry-class.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="UncondNeighborhood-class">
-<param name="Local" value="UncondNeighborhood-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="width">
-<param name="Local" value="asUnOvShoot-class.html">
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-<param name="Name" value="width,asUnOvShoot-method">
-<param name="Local" value="asUnOvShoot-class.html">
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-<param name="Name" value="width,fiUnOvShoot-method">
-<param name="Local" value="fiUnOvShoot-class.html">
-</OBJECT>
</UL>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Package ROptEst: Titles">
</OBJECT>
<UL>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="asymmetric Bias Type">
-<param name="Local" value="asymmetricBiasType-class.html">
+<param name="Name" value="Calculation of L1 norm of L2derivative">
+<param name="Local" value="getL1normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Asymptotic covariance">
-<param name="Local" value="asCov-class.html">
+<param name="Name" value="Calculation of L2 norm of L2derivative">
+<param name="Local" value="getL2normL2deriv.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Asymptotic Hampel risk">
-<param name="Local" value="asHampel-class.html">
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-<param name="Name" value="Asymptotic mean square error">
-<param name="Local" value="asMSE-class.html">
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-<param name="Name" value="Asymptotic under-/overshoot probability">
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-<param name="Name" value="Aymptotic risk">
-<param name="Local" value="asRisk-class.html">
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-<param name="Name" value="Bias Type">
-<param name="Local" value="BiasType-class.html">
-</OBJECT>
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-<param name="Name" value="Class for Elliptically Symmetric Distributions">
-<param name="Local" value="EllipticalSymmetry-class.html">
-</OBJECT>
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-<param name="Name" value="Class for Even Functions">
-<param name="Local" value="EvenSymmetric-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Class for Non-symmetric Distributions">
-<param name="Local" value="NoSymmetry-class.html">
-</OBJECT>
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-<param name="Name" value="Class for Non-symmetric Functions">
-<param name="Local" value="NonSymmetric-class.html">
-</OBJECT>
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-<param name="Name" value="Class for Odd Functions">
-<param name="Local" value="OddSymmetric-class.html">
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-<param name="Name" value="Class for Spherical Symmetric Distributions">
-<param name="Local" value="SphericalSymmetry-class.html">
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-<param name="Name" value="Class of Symmetries">
-<param name="Local" value="Symmetry-class.html">
-</OBJECT>
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-<param name="Name" value="Class of Symmetries for Distributions">
-<param name="Local" value="DistributionSymmetry-class.html">
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-<param name="Name" value="Class of Symmetries for Functions">
-<param name="Local" value="FunctionSymmetry-class.html">
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<param name="Name" value="Computation of the lower case radius">
<param name="Local" value="lowerCaseRadius.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
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-<param name="Name" value="Convex asymptotic risk">
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-<param name="Name" value="Family of probability measures">
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-<param name="Name" value="Finite-sample Bias">
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-<param name="Name" value="Finite-sample covariance">
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-<param name="Name" value="Finite-sample Hampel risk">
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-<param name="Name" value="Finite-sample mean square error">
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-<param name="Name" value="Finite-sample risk">
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-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for asBias-class">
-<param name="Local" value="asBias.html">
-</OBJECT>
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-<param name="Name" value="Generating function for asCov-class">
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-<param name="Name" value="Generating function for asHampel-class">
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-<param name="Name" value="Generating function for asUnOvShoot-class">
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-<param name="Local" value="asymmetricBias.html">
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-<param name="Name" value="Generating function for Binomial families">
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-<param name="Name" value="Generating function for ContIC-class">
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-<param name="Name" value="Generating function for fiMSE-class">
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-<param name="Name" value="Generating function for fiUnOvShoot-class">
-<param name="Local" value="fiUnOvShoot.html">
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-<param name="Name" value="Generating function for FixRobModel-class">
-<param name="Local" value="FixRobModel.html">
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-<param name="Name" value="Generating function for FunSymmList-class">
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-<param name="Name" value="Generating function for Gamma families">
-<param name="Local" value="GammaFamily.html">
-</OBJECT>
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-<param name="Name" value="Generating function for Gumbel location families">
-<param name="Local" value="GumbelLocationFamily.html">
-</OBJECT>
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-<param name="Name" value="Generating function for IC-class">
-<param name="Local" value="IC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for InfluenceCurve-class">
-<param name="Local" value="InfluenceCurve.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for InfRobModel-class">
-<param name="Local" value="InfRobModel.html">
-</OBJECT>
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-<param name="Name" value="Generating function for L2ParamFamily-class">
-<param name="Local" value="L2ParamFamily.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for lognormal scale families">
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-<param name="Name" value="Generating function for normal location and scale families">
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-<param name="Name" value="Generating function for normal location families">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for normal scale families">
-<param name="Local" value="NormScaleFamily.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for NoSymmetry-class">
-<param name="Local" value="NoSymmetry.html">
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-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for OddSymmetric-class">
-<param name="Local" value="OddSymmetric.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for onesidedBiasType-class">
-<param name="Local" value="positiveBias.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for ParamFamily-class">
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-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for ParamFamParameter-class">
-<param name="Local" value="ParamFamParameter.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for Poisson families">
-<param name="Local" value="PoisFamily.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for PosDefSymmMatrix-class">
-<param name="Local" value="PosDefSymmMatrix.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for SphericalSymmetry-class">
-<param name="Local" value="SphericalSymmetry.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for symmetricBias-class">
-<param name="Local" value="symmetricBias.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for TotalVarIC-class">
-<param name="Local" value="TotalVarIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for TotalVarNeighborhood-class">
-<param name="Local" value="TotalVarNeighborhood.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for trAsCov-class">
-<param name="Local" value="trAsCov.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generating function for trFiCov-class">
-<param name="Local" value="trFiCov.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic Function for Checking ICs">
-<param name="Local" value="checkIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic function for checking L2-derivatives">
-<param name="Local" value="checkL2deriv.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic Function for Computation of Asymptotic Risks">
<param name="Local" value="getAsRisk.html">
</OBJECT>
@@ -1815,14 +535,14 @@
<param name="Local" value="getFiRisk.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic function for evaluating ICs">
-<param name="Local" value="evalIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the computation of a risk for an IC">
<param name="Local" value="getRiskIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic Function for the Computation of Bias-Optimally Robust ICs ">
+<param name="Local" value="minmaxBias.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic Function for the Computation of Inefficiency Differences">
<param name="Local" value="getIneffDiff.html">
</OBJECT>
@@ -1835,10 +555,6 @@
<param name="Local" value="locMEstimator.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic function for the computation of one-step estimators">
-<param name="Local" value="oneStepEstimator.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the computation of optimally robust ICs">
<param name="Local" value="optIC.html">
</OBJECT>
@@ -1847,8 +563,8 @@
<param name="Local" value="getInfRobIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator">
-<param name="Local" value="ksEstimator.html">
+<param name="Name" value="Generic function for the computation of the asymptotic bias for an IC">
+<param name="Local" value="getBiasIC.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the computation of the minimal risk">
@@ -1871,90 +587,6 @@
<param name="Local" value="getInfStand.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic function for the generation of influence curves">
-<param name="Local" value="generateIC.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Influence curve">
-<param name="Local" value="InfluenceCurve-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Influence curve of contamination type">
-<param name="Local" value="ContIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Influence curve of total variation type">
-<param name="Local" value="TotalVarIC-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="L2 differentiable parametric family">
-<param name="Local" value="L2ParamFamily-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="List of Symmetries for a List of Distributions">
-<param name="Local" value="DistrSymmList-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="List of Symmetries for a List of Functions">
-<param name="Local" value="FunSymmList-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Neighborhood">
-<param name="Local" value="Neighborhood-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="onesided Bias Type">
-<param name="Local" value="onesidedBiasType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Optional numeric">
-<param name="Local" value="OptionalNumeric-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Parameter of a parametric family of probability measures">
-<param name="Local" value="ParamFamParameter-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Parametric family of probability measures.">
-<param name="Local" value="ParamFamily-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Plot absolute and relative information">
-<param name="Local" value="infoPlot.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Positive-definite, symmetric matrices">
-<param name="Local" value="PosDefSymmMatrix-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Risk">
-<param name="Local" value="RiskType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Robust model">
-<param name="Local" value="RobModel-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Robust model with fixed (unconditional) neighborhood">
-<param name="Local" value="FixRobModel-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Robust model with infinitesimal (unconditional) neighborhood">
-<param name="Local" value="InfRobModel-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Standardized Asymptotic Bias">
-<param name="Local" value="asBias-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="symmetric Bias Type">
-<param name="Local" value="symmetricBiasType-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Total variation neighborhood">
-<param name="Local" value="TotalVarNeighborhood-class.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Trace of asymptotic covariance">
<param name="Local" value="trAsCov-class.html">
</OBJECT>
@@ -1962,10 +594,6 @@
<param name="Name" value="Trace of finite-sample covariance">
<param name="Local" value="trFiCov-class.html">
</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Unconditional neighborhood">
-<param name="Local" value="UncondNeighborhood-class.html">
-</OBJECT>
</UL>
</UL>
</BODY></HTML>
Deleted: pkg/ROptEst/chm/RiskType-class.html
===================================================================
--- pkg/ROptEst/chm/RiskType-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/RiskType-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,57 +0,0 @@
-<html><head><title>Risk</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>RiskType-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: RiskType-class">
-<param name="keyword" value="R: show,RiskType-method">
-<param name="keyword" value="R: type,RiskType-method">
-<param name="keyword" value=" Risk">
-</object>
-
-
-<h2>Risk</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of risks; e.g., estimator risks.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-type of risk. </dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>type</dt><dd><code>signature(object = "RiskType")</code>:
-accessor function for slot <code>type</code>. </dd>
-<dt>show</dt><dd><code>signature(object = "RiskType")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/RobModel-class.html
===================================================================
--- pkg/ROptEst/chm/RobModel-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/RobModel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,89 +0,0 @@
-<html><head><title>Robust model</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>RobModel-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: RobModel-class">
-<param name="keyword" value="R: center">
-<param name="keyword" value="R: center,RobModel-method">
-<param name="keyword" value="R: center<-">
-<param name="keyword" value="R: center<-,RobModel-method">
-<param name="keyword" value="R: name,RobModel-method">
-<param name="keyword" value="R: neighbor">
-<param name="keyword" value="R: neighbor,RobModel-method">
-<param name="keyword" value="R: neighbor<-">
-<param name="keyword" value="R: neighbor<-,RobModel-method">
-<param name="keyword" value=" Robust model">
-</object>
-
-
-<h2>Robust model</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of robust models. A robust model consists
-of family of probability measures <code>center</code> and a
-neighborhood <code>neighbor</code> about this family.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>center</code>:</dt><dd>Object of class <code>"ProbFamily"</code> </dd>
-<dt><code>neighbor</code>:</dt><dd>Object of class <code>"Neighborhood"</code></dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>center</dt><dd><code>signature(object = "RobModel")</code>:
-accessor function for slot <code>center</code>. </dd>
-<dt>center<-</dt><dd><code>signature(object = "RobModel")</code>:
-replacement function for slot <code>center</code>. </dd>
-<dt>neighbor</dt><dd><code>signature(object = "RobModel")</code>:
-accessor function for slot <code>neighbor</code>. </dd>
-<dt>neighbor<-</dt><dd><code>signature(object = "RobModel")</code>:
-replacement function for slot <code>neighbor</code>. </dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="ProbFamily-class.html">ProbFamily-class</a></code>, <code><a href="Neighborhood-class.html">Neighborhood-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/SphericalSymmetry-class.html
===================================================================
--- pkg/ROptEst/chm/SphericalSymmetry-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/SphericalSymmetry-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,75 +0,0 @@
-<html><head><title>Class for Spherical Symmetric Distributions</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>SphericalSymmetry-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: SphericalSymmetry-class">
-<param name="keyword" value=" Class for Spherical Symmetric Distributions">
-</object>
-
-
-<h2>Class for Spherical Symmetric Distributions</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class for spherical symmetric distributions.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("SphericalSymmetry")</code>.
-More frequently they are created via the generating function
-<code>SphericalSymmetry</code>. Spherical symmetry for instance leads to
-a simplification for the computation of optimally robust influence curves.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-contains “spherical symmetric distribution” </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"numeric"</code>:
-center of symmetry </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"EllipticalSymmetry"</code>, directly.<br>
-Class <code>"DistributionSymmetry"</code>, by class <code>"EllipticalSymmetry"</code>.<br>
-Class <code>"Symmetry"</code>, by class <code>"EllipticalSymmetry"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="SphericalSymmetry.html">SphericalSymmetry</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("SphericalSymmetry")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/SphericalSymmetry.html
===================================================================
--- pkg/ROptEst/chm/SphericalSymmetry.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/SphericalSymmetry.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,70 +0,0 @@
-<html><head><title>Generating function for SphericalSymmetry-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>SphericalSymmetry(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: SphericalSymmetry">
-<param name="keyword" value=" Generating function for SphericalSymmetry-class">
-</object>
-
-
-<h2>Generating function for SphericalSymmetry-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"SphericalSymmetry"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>SphericalSymmetry(SymmCenter = 0)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>SymmCenter</code></td>
-<td>
-numeric: center of symmetry </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"SphericalSymmetry"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="SphericalSymmetry-class.html">SphericalSymmetry-class</a></code>, <code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-SphericalSymmetry()
-
-## The function is currently defined as
-function(SymmCenter = 0){
- new("SphericalSymmetry", SymmCenter = SymmCenter)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/Symmetry-class.html
===================================================================
--- pkg/ROptEst/chm/Symmetry-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/Symmetry-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,76 +0,0 @@
-<html><head><title>Class of Symmetries</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>Symmetry-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: Symmetry-class">
-<param name="keyword" value="R: show,Symmetry-method">
-<param name="keyword" value="R: type">
-<param name="keyword" value="R: type,Symmetry-method">
-<param name="keyword" value="R: SymmCenter">
-<param name="keyword" value="R: SymmCenter,Symmetry-method">
-<param name="keyword" value=" Class of Symmetries">
-</object>
-
-
-<h2>Class of Symmetries</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of symmetries of various objects.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-discribes type of symmetry. </dd>
-<dt><code>SymmCenter</code>:</dt><dd>Object of class <code>"ANY"</code>:
-center of symmetry. </dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>type</dt><dd><code>signature(object = "Symmetry")</code>:
-accessor function for slot <code>type</code></dd>
-
-
-<dt>SymmCenter</dt><dd><code>signature(object = "Symmetry")</code>:
-accessor function for slot <code>SymmCenter</code></dd>
-
-
-<dt>show</dt><dd><code>signature(object = "Symmetry")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="DistributionSymmetry-class.html">DistributionSymmetry-class</a></code>, <code><a href="FunctionSymmetry-class.html">FunctionSymmetry-class</a></code>,
-<code><a href="OptionalNumeric-class.html">OptionalNumeric-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/TotalVarIC-class.html
===================================================================
--- pkg/ROptEst/chm/TotalVarIC-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/TotalVarIC-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,185 +0,0 @@
-<html><head><title>Influence curve of total variation type</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>TotalVarIC-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: TotalVarIC-class">
-<param name="keyword" value="R: CallL2Fam<-,TotalVarIC-method">
-<param name="keyword" value="R: clipLo">
-<param name="keyword" value="R: clipLo,TotalVarIC-method">
-<param name="keyword" value="R: clipLo<-">
-<param name="keyword" value="R: clipLo<-,TotalVarIC-method">
-<param name="keyword" value="R: clipUp">
-<param name="keyword" value="R: clipUp,TotalVarIC-method">
-<param name="keyword" value="R: clipUp<-">
-<param name="keyword" value="R: clipUp<-,TotalVarIC-method">
-<param name="keyword" value="R: lowerCase,TotalVarIC-method">
-<param name="keyword" value="R: lowerCase<-,TotalVarIC-method">
-<param name="keyword" value="R: neighborRadius,TotalVarIC-method">
-<param name="keyword" value="R: neighborRadius<-,TotalVarIC-method">
-<param name="keyword" value="R: show,TotalVarIC-method">
-<param name="keyword" value="R: stand,TotalVarIC-method">
-<param name="keyword" value="R: stand<-,TotalVarIC-method">
-<param name="keyword" value="R: generateIC,TotalVarNeighborhood,L2ParamFamily-method">
-<param name="keyword" value=" Influence curve of total variation type">
-</object>
-
-
-<h2>Influence curve of total variation type</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of (partial) influence curves of total variation type.
-i.e., an influence curves <i>eta</i> of the form
-</p><p align="center"><i>eta = max(c, min(A Lambda, d))</i></p><p>
-with lower clipping bound <i>c</i>, upper clipping bound <i>d</i> and
-standardizing matrix <i>A</i>. <i>Lambda</i> stands for
-the L2 derivative of the corresponding L2 differentiable
-parametric family which can be created via <code>CallL2Fam</code>.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("TotalVarIC", ...)</code>.
-More frequently they are created via the generating function
-<code>TotalVarIC</code>, respectively via the method <code>generateIC</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>CallL2Fam</code>:</dt><dd>object of class <code>"call"</code>:
-creates an object of the underlying L2-differentiable
-parametric family. </dd>
-
-
-<dt><code>name</code>:</dt><dd>object of class <code>"character"</code>. </dd>
-
-
-<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code>.</dd>
-
-
-<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </dd>
-
-
-<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
-with two columns named <code>method</code> and <code>message</code>:
-additional informations. </dd>
-
-
-<dt><code>clipLo</code>:</dt><dd>object of class <code>"numeric"</code>:
-lower clipping bound. </dd>
-
-
-<dt><code>clipUp</code>:</dt><dd>object of class <code>"numeric"</code>:
-upper clipping bound. </dd>
-
-
-<dt><code>stand</code>:</dt><dd>object of class <code>"matrix"</code>:
-standardizing matrix. </dd>
-
-
-<dt><code>neighborRadius</code>:</dt><dd>object of class <code>"numeric"</code>:
-radius of the corresponding (unconditional) contamination
-neighborhood. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"IC"</code>, directly.<br>
-Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>CallL2Fam<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
-replacement function for slot <code>CallL2Fam</code>. </dd>
-
-
-<dt>clipLo</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>clipLo</code>. </dd>
-
-
-<dt>clipLo<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
-replacement function for slot <code>clipLo</code>. </dd>
-
-
-<dt>clipUp</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>clipUp</code>. </dd>
-
-
-<dt>clipUp<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
-replacement function for slot <code>clipUp</code>. </dd>
-
-
-<dt>stand</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>stand</code>. </dd>
-
-
-<dt>stand<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
-replacement function for slot <code>stand</code>. </dd>
-
-
-<dt>neighborRadius</dt><dd><code>signature(object = "TotalVarIC")</code>:
-accessor function for slot <code>neighborRadius</code>. </dd>
-
-
-<dt>neighborRadius<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
-replacement function for slot <code>neighborRadius</code>. </dd>
-
-
-<dt>generateIC</dt><dd><code>signature(neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily")</code>:
-generate an object of class <code>"TotalVarIC"</code>. Rarely called directly. </dd>
-
-
-<dt>show</dt><dd><code>signature(object = "TotalVarIC")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- new("TotalVarIC")
-plot(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/TotalVarIC.html
===================================================================
--- pkg/ROptEst/chm/TotalVarIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/TotalVarIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,121 +0,0 @@
-<html><head><title>Generating function for TotalVarIC-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>TotalVarIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: TotalVarIC">
-<param name="keyword" value=" Generating function for TotalVarIC-class">
-</object>
-
-
-<h2>Generating function for TotalVarIC-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"TotalVarIC"</code>;
-i.e., an influence curves <i>eta</i> of the form
-</p><p align="center"><i>eta = max(c, min(A Lambda, d))</i></p><p>
-with lower clipping bound <i>c</i>, upper clipping bound <i>d</i> and
-standardizing matrix <i>A</i>. <i>Lambda</i> stands for
-the L2 derivative of the corresponding L2 differentiable
-parametric family which can be created via <code>CallL2Fam</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-TotalVarIC(name, CallL2Fam = call("L2ParamFamily"),
- Curve = EuclRandVarList(RealRandVariable(Map = c(function(x) {x}),
- Domain = Reals())),
- Risks, Infos, clipLo = -Inf, clipUp = Inf, stand = as.matrix(1),
- lowerCase = NULL, neighborRadius = 0)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-object of class <code>"character"</code>. </td></tr>
-<tr valign="top"><td><code>CallL2Fam</code></td>
-<td>
-object of class <code>"call"</code>:
-creates an object of the underlying L2-differentiable
-parametric family. </td></tr>
-<tr valign="top"><td><code>Curve</code></td>
-<td>
-object of class <code>"EuclRandVarList"</code>. </td></tr>
-<tr valign="top"><td><code>Risks</code></td>
-<td>
-object of class <code>"list"</code>:
-list of risks; cf. <code><a href="RiskType-class.html">RiskType-class</a></code>. </td></tr>
-<tr valign="top"><td><code>Infos</code></td>
-<td>
-matrix of characters with two columns
-named <code>method</code> and <code>message</code>: additional informations. </td></tr>
-<tr valign="top"><td><code>clipLo</code></td>
-<td>
-negative real: lower clipping bound. </td></tr>
-<tr valign="top"><td><code>clipUp</code></td>
-<td>
-positive real: lower clipping bound. </td></tr>
-<tr valign="top"><td><code>stand</code></td>
-<td>
-matrix: standardizing matrix </td></tr>
-<tr valign="top"><td><code>lowerCase</code></td>
-<td>
-optional constant for lower case solution. </td></tr>
-<tr valign="top"><td><code>neighborRadius</code></td>
-<td>
-radius of the corresponding (unconditional)
-contamination neighborhood. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"TotalVarIC"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- TotalVarIC()
-plot(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/TotalVarNeighborhood-class.html
===================================================================
--- pkg/ROptEst/chm/TotalVarNeighborhood-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/TotalVarNeighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,91 +0,0 @@
-<html><head><title>Total variation neighborhood</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>TotalVarNeighborhood-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: TotalVarNeighborhood-class">
-<param name="keyword" value=" Total variation neighborhood">
-</object>
-
-
-<h2>Total variation neighborhood</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of (unconditional) total variation neighborhoods.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("TotalVarNeighborhood", ...)</code>.
-More frequently they are created via the generating function
-<code>TotalVarNeighborhood</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“(uncond.) total variation neighborhood”. </dd>
-<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
-neighborhood radius. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"UncondNeighborhood"</code>, directly.<br>
-Class <code>"Neighborhood"</code>, by class <code>"UncondNeighborhood"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "TotalVarNeighborhood" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="TotalVarNeighborhood.html">TotalVarNeighborhood</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("TotalVarNeighborhood")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/TotalVarNeighborhood.html
===================================================================
--- pkg/ROptEst/chm/TotalVarNeighborhood.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/TotalVarNeighborhood.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,81 +0,0 @@
-<html><head><title>Generating function for TotalVarNeighborhood-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>TotalVarNeighborhood(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: TotalVarNeighborhood">
-<param name="keyword" value=" Generating function for TotalVarNeighborhood-class">
-</object>
-
-
-<h2>Generating function for TotalVarNeighborhood-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"TotalVarNeighborhood"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>TotalVarNeighborhood(radius = 0)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>radius</code></td>
-<td>
-non-negative real: neighborhood radius. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"ContNeighborhood"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="TotalVarNeighborhood-class.html">TotalVarNeighborhood-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-TotalVarNeighborhood()
-
-## The function is currently defined as
-function(radius = 0){
- new("TotalVarNeighborhood", radius = radius)
-}
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/UncondNeighborhood-class.html
===================================================================
--- pkg/ROptEst/chm/UncondNeighborhood-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/UncondNeighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,74 +0,0 @@
-<html><head><title>Unconditional neighborhood</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>UncondNeighborhood-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: UncondNeighborhood-class">
-<param name="keyword" value=" Unconditional neighborhood">
-</object>
-
-
-<h2>Unconditional neighborhood</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of unconditonal (errors-in-variables) neighborhoods.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-type of the neighborhood. </dd>
-<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
-neighborhood radius. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"Neighborhood"</code>, directly.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="Neighborhood-class.html">Neighborhood-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asBias-class.html
===================================================================
--- pkg/ROptEst/chm/asBias-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asBias-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Standardized Asymptotic Bias</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asBias-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asBias-class">
-<param name="keyword" value=" Standardized Asymptotic Bias">
-</object>
-
-
-<h2>Standardized Asymptotic Bias</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of standardized asymptotic bias; i.e.,
-the neighborhood radius is omitted respectively, set to <i>1</i>.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("asBias", ...)</code>.
-More frequently they are created via the generating function
-<code>asBias</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“asymptotic bias”. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"asRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"asRisk"</code>.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asRisk-class.html">asRisk-class</a></code>, <code><a href="asBias.html">asBias</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("asBias")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asBias.html
===================================================================
--- pkg/ROptEst/chm/asBias.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,71 +0,0 @@
-<html><head><title>Generating function for asBias-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asBias">
-<param name="keyword" value=" Generating function for asBias-class">
-</object>
-
-
-<h2>Generating function for asBias-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"asBias"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asBias()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"asBias"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asBias-class.html">asBias-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asBias()
-
-## The function is currently defined as
-function(){ new("asBias") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asCov-class.html
===================================================================
--- pkg/ROptEst/chm/asCov-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asCov-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,89 +0,0 @@
-<html><head><title>Asymptotic covariance</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asCov-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asCov-class">
-<param name="keyword" value=" Asymptotic covariance">
-</object>
-
-
-<h2>Asymptotic covariance</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymptotic covariance.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("asCov", ...)</code>.
-More frequently they are created via the generating function
-<code>asCov</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“asymptotic covariance”. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"asRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"asRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "asCov" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asRisk-class.html">asRisk-class</a></code>, <code><a href="asCov.html">asCov</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("asCov")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asCov.html
===================================================================
--- pkg/ROptEst/chm/asCov.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asCov.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,71 +0,0 @@
-<html><head><title>Generating function for asCov-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asCov(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asCov">
-<param name="keyword" value=" Generating function for asCov-class">
-</object>
-
-
-<h2>Generating function for asCov-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"asCov"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asCov()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"asCov"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asCov-class.html">asCov-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asCov()
-
-## The function is currently defined as
-function(){ new("asCov") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asGRisk-class.html
===================================================================
--- pkg/ROptEst/chm/asGRisk-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asGRisk-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,76 +0,0 @@
-<html><head><title>Convex asymptotic risk</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asGRisk-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asGRisk-class">
-<param name="keyword" value=" Convex asymptotic risk">
-</object>
-
-
-<h2>Convex asymptotic risk</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of special convex asymptotic risks.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"asRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"asRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "asGRisk" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
-General Loss Functions. Statistics & Decisions (submitted).
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asRisk-class.html">asRisk-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asHampel-class.html
===================================================================
--- pkg/ROptEst/chm/asHampel-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asHampel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,101 +0,0 @@
-<html><head><title>Asymptotic Hampel risk</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asHampel-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asHampel-class">
-<param name="keyword" value="R: bound">
-<param name="keyword" value="R: bound,asHampel-method">
-<param name="keyword" value="R: show,asHampel-method">
-<param name="keyword" value=" Asymptotic Hampel risk">
-</object>
-
-
-<h2>Asymptotic Hampel risk</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymptotic Hampel risk which is
-the trace of the asymptotic covariance subject to
-a given bias bound (bound on gross error sensitivity).
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("asHampel", ...)</code>.
-More frequently they are created via the generating function
-<code>asHampel</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“trace of asymptotic covariance for given bias bound”. </dd>
-<dt><code>bound</code>:</dt><dd>Object of class <code>"numeric"</code>:
-given positive bias bound. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"asRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"asRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>bound</dt><dd><code>signature(object = "asHampel")</code>:
-accessor function for slot <code>bound</code>. </dd>
-<dt>show</dt><dd><code>signature(object = "asHampel")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asRisk-class.html">asRisk-class</a></code>, <code><a href="asHampel.html">asHampel</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("asHampel")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asHampel.html
===================================================================
--- pkg/ROptEst/chm/asHampel.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asHampel.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Generating function for asHampel-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asHampel(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asHampel">
-<param name="keyword" value=" Generating function for asHampel-class">
-</object>
-
-
-<h2>Generating function for asHampel-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"asHampel"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asHampel(bound = Inf)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>bound</code></td>
-<td>
-positive real: bias bound </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>asHampel</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asHampel-class.html">asHampel-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asHampel()
-
-## The function is currently defined as
-function(bound = Inf){ new("asHampel", bound = bound) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asMSE-class.html
===================================================================
--- pkg/ROptEst/chm/asMSE-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asMSE-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,90 +0,0 @@
-<html><head><title>Asymptotic mean square error</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asMSE-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asMSE-class">
-<param name="keyword" value=" Asymptotic mean square error">
-</object>
-
-
-<h2>Asymptotic mean square error</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymptotic mean square error.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("asMSE", ...)</code>.
-More frequently they are created via the generating function
-<code>asMSE</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“asymptotic mean square error”. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"asGRisk"</code>, directly.<br>
-Class <code>"asRisk"</code>, by class <code>"asGRisk"</code>.<br>
-Class <code>"RiskType"</code>, by class <code>"asGRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "asMSE" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asGRisk-class.html">asGRisk-class</a></code>, <code><a href="asMSE.html">asMSE</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("asMSE")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asMSE.html
===================================================================
--- pkg/ROptEst/chm/asMSE.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asMSE.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,71 +0,0 @@
-<html><head><title>Generating function for asMSE-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asMSE(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asMSE">
-<param name="keyword" value=" Generating function for asMSE-class">
-</object>
-
-
-<h2>Generating function for asMSE-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"asMSE"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asMSE()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"asMSE"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asMSE-class.html">asMSE-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asMSE()
-
-## The function is currently defined as
-function(){ new("asMSE") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asRisk-class.html
===================================================================
--- pkg/ROptEst/chm/asRisk-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asRisk-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,82 +0,0 @@
-<html><head><title>Aymptotic risk</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asRisk-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asRisk-class">
-<param name="keyword" value=" Aymptotic risk">
-</object>
-
-
-<h2>Aymptotic risk</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymptotic risks.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>.</dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"RiskType"</code>, directly.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "asRisk" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
-General Loss Functions. Statistics & Decisions (submitted).
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="RiskType-class.html">RiskType-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asUnOvShoot-class.html
===================================================================
--- pkg/ROptEst/chm/asUnOvShoot-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asUnOvShoot-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,96 +0,0 @@
-<html><head><title>Asymptotic under-/overshoot probability</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asUnOvShoot-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asUnOvShoot-class">
-<param name="keyword" value="R: width">
-<param name="keyword" value="R: width,asUnOvShoot-method">
-<param name="keyword" value="R: show,asUnOvShoot-method">
-<param name="keyword" value=" Asymptotic under-/overshoot probability">
-</object>
-
-
-<h2>Asymptotic under-/overshoot probability</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymptotic under-/overshoot probability.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("asUnOvShoot", ...)</code>.
-More frequently they are created via the generating function
-<code>asUnOvShoot</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-dQuote{asymptotic under-/overshoot probability}. </dd>
-<dt><code>width</code>:</dt><dd>Object of class <code>"numeric"</code>:
-half the width of given confidence interval. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"asGRisk"</code>, directly.<br>
-Class <code>"asRisk"</code>, by class <code>"asGRisk"</code>.<br>
-Class <code>"RiskType"</code>, by class <code>"asGRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>width</dt><dd><code>signature(object = "asUnOvShoot")</code>:
-accessor function for slot <code>width</code>. </dd>
-<dt>show</dt><dd><code>signature(object = "asUnOvShoot")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asGRisk-class.html">asGRisk-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("asUnOvShoot")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asUnOvShoot.html
===================================================================
--- pkg/ROptEst/chm/asUnOvShoot.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asUnOvShoot.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,79 +0,0 @@
-<html><head><title>Generating function for asUnOvShoot-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asUnOvShoot(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asUnOvShoot">
-<param name="keyword" value=" Generating function for asUnOvShoot-class">
-</object>
-
-
-<h2>Generating function for asUnOvShoot-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"asUnOvShoot"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asUnOvShoot(width = 1.960)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>width</code></td>
-<td>
-positive real: half the width of given confidence interval. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"asUnOvShoot"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asUnOvShoot-class.html">asUnOvShoot-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asUnOvShoot()
-
-## The function is currently defined as
-function(width = 1.960){ new("asUnOvShoot", width = width) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asymmetricBias.html
===================================================================
--- pkg/ROptEst/chm/asymmetricBias.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asymmetricBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-<html><head><title>Generating function for asymmetricBiasType-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asymmetricBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asymmetricBias">
-<param name="keyword" value=" Generating function for asymmetricBiasType-class">
-</object>
-
-
-<h2>Generating function for asymmetricBiasType-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"asymmetricBiasType"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asymmetricBias(name = "asymmetric Bias", nu = c(1,1) )</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-name of the bias type</td></tr>
-<tr valign="top"><td><code>nu</code></td>
-<td>
-weights for negative and positive bias, respectively</td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"asymmetricBiasType"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="asymmetricBiasType-class.html">asymmetricBiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asymmetricBias()
-
-## The function is currently defined as
-function(){ new("asymmetricBiasType", name = "asymmetric Bias", nu = c(1,1)) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/asymmetricBiasType-class.html
===================================================================
--- pkg/ROptEst/chm/asymmetricBiasType-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/asymmetricBiasType-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,107 +0,0 @@
-<html><head><title>asymmetric Bias Type</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>asymmetricBiasType-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: asymmetricBiasType-class">
-<param name="keyword" value="R: nu,asymmetricBiasType-method">
-<param name="keyword" value="R: nu<-,asymmetricBiasType-method">
-<param name="keyword" value="R: nu">
-<param name="keyword" value="R: nu<-">
-<param name="keyword" value=" asymmetric Bias Type">
-</object>
-
-
-<h2>asymmetric Bias Type</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymmetric bias types.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("asymmetricBiasType", ...)</code>.
-More frequently they are created via the generating function
-<code>asymmetricBias</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>.</dd>
-<dt><code>nu</code>:</dt><dd>Object of class <code>"numeric"</code>;
-to be in (0,1] x (0,1] with maximum 1; weights for
-negative and positive bias, respectively</dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>nu</dt><dd><code>signature(object = "asymmetricBiasType")</code>:
-accessor function for slot <code>nu</code>. </dd>
-<dt>nu<-</dt><dd><code>signature(object = "asymmetricBiasType", value = "numeric")</code>:
-replacement function for slot <code>nu</code>. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"BiasType"</code>, directly.<br>
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="BiasType-class.html">BiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-asymmetricBias()
-## The function is currently defined as
-function(){ new("asymmetricBiasType", name = "asymmetric Bias", nu = c(1,1)) }
-
-aB <- asymmetricBias()
-nu(aB)
-try(nu(aB) <- -2) ## error
-nu(aB) <- c(0.3,1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/checkIC.html
===================================================================
--- pkg/ROptEst/chm/checkIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/checkIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,94 +0,0 @@
-<html><head><title>Generic Function for Checking ICs</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>checkIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: checkIC">
-<param name="keyword" value=" Generic Function for Checking ICs">
-</object>
-
-
-<h2>Generic Function for Checking ICs</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generic function for checking centering and Fisher
-consistency of ICs.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-checkIC(IC, L2Fam, ...)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>IC</code></td>
-<td>
-object of class <code>"IC"</code> </td></tr>
-<tr valign="top"><td><code>L2Fam</code></td>
-<td>
-L2-differentiable family of probability measures. </td></tr>
-<tr valign="top"><td><code>...</code></td>
-<td>
-additional parameters </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The precisions of the centering and the Fisher consistency
-are computed.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-The maximum deviation from the IC properties is returned.</p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a href="IC-class.html">IC-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-IC1 <- new("IC")
-checkIC(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/checkL2deriv.html
===================================================================
--- pkg/ROptEst/chm/checkL2deriv.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/checkL2deriv.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,91 +0,0 @@
-<html><head><title>Generic function for checking L2-derivatives</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>checkL2deriv(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: checkL2deriv">
-<param name="keyword" value=" Generic function for checking L2-derivatives">
-</object>
-
-
-<h2>Generic function for checking L2-derivatives</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generic function for checking the L2-derivative of
-an L2-differentiable family of probability measures.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-checkL2deriv(L2Fam, ...)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>L2Fam</code></td>
-<td>
-L2-differentiable family of probability measures </td></tr>
-<tr valign="top"><td><code>...</code></td>
-<td>
-additional parameters </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The precisions of the centering and the Fisher information
-are computed.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-The maximum deviation is returned.</p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-F1 <- new("L2ParamFamily")
-checkL2deriv(F1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/evalIC.html
===================================================================
--- pkg/ROptEst/chm/evalIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/evalIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Generic function for evaluating ICs</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>evalIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: evalIC">
-<param name="keyword" value=" Generic function for evaluating ICs">
-</object>
-
-
-<h2>Generic function for evaluating ICs</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generic function for evaluating ICs.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-evalIC(IC, x)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>IC</code></td>
-<td>
-object of class <code>"IC"</code> </td></tr>
-<tr valign="top"><td><code>x</code></td>
-<td>
-numeric vector or matrix </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-The list of random variables contained in the slot <code>Curve</code>
-is evaluated at <code>x</code>.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-In case <code>x</code> is numeric a vector and in case <code>x</code>
-is matrix a matrix is returned.</p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiBias-class.html
===================================================================
--- pkg/ROptEst/chm/fiBias-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiBias-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-<html><head><title>Finite-sample Bias</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiBias-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiBias-class">
-<param name="keyword" value=" Finite-sample Bias">
-</object>
-
-
-<h2>Finite-sample Bias</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of finite-sample bias.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("fiBias", ...)</code>.
-More frequently they are created via the generating function
-<code>fiBias</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“finite-sample bias”. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"fiRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"fiRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "fiBias" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>, <code><a href="fiBias.html">fiBias</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("fiBias")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiBias.html
===================================================================
--- pkg/ROptEst/chm/fiBias.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,68 +0,0 @@
-<html><head><title>Generating function for fiBias-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiBias">
-<param name="keyword" value=" Generating function for fiBias-class">
-</object>
-
-
-<h2>Generating function for fiBias-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"fiBias"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>fiBias()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"fiBias"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiBias-class.html">fiBias-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-fiBias()
-
-## The function is currently defined as
-function(){ new("fiBias") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiCov-class.html
===================================================================
--- pkg/ROptEst/chm/fiCov-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiCov-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-<html><head><title>Finite-sample covariance</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiCov-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiCov-class">
-<param name="keyword" value=" Finite-sample covariance">
-</object>
-
-
-<h2>Finite-sample covariance</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of finite-sample covariance.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("fiCov", ...)</code>.
-More frequently they are created via the generating function
-<code>fiCov</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“finite-sample covariance”. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"fiRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"fiRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "fiCov" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>, <code><a href="fiCov.html">fiCov</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("fiCov")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiCov.html
===================================================================
--- pkg/ROptEst/chm/fiCov.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiCov.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,68 +0,0 @@
-<html><head><title>Generating function for fiCov-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiCov(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiCov">
-<param name="keyword" value=" Generating function for fiCov-class">
-</object>
-
-
-<h2>Generating function for fiCov-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"fiCov"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asCov()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"fiCov"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiCov-class.html">fiCov-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-fiCov()
-
-## The function is currently defined as
-function(){ new("fiCov") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiHampel-class.html
===================================================================
--- pkg/ROptEst/chm/fiHampel-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiHampel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,97 +0,0 @@
-<html><head><title>Finite-sample Hampel risk</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiHampel-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiHampel-class">
-<param name="keyword" value="R: bound,fiHampel-method">
-<param name="keyword" value="R: show,fiHampel-method">
-<param name="keyword" value=" Finite-sample Hampel risk">
-</object>
-
-
-<h2>Finite-sample Hampel risk</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of finite-sample Hampel risk which is
-the trace of the finite-sample covariance subject to
-a given bias bound (bound on gross error sensitivity).
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("fiHampel", ...)</code>.
-More frequently they are created via the generating function
-<code>fiHampel</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“trace of finite-sample covariance for given bias bound”. </dd>
-<dt><code>bound</code>:</dt><dd>Object of class <code>"numeric"</code>:
-given positive bias bound. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"fiRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"fiRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>bound</dt><dd><code>signature(object = "fiHampel")</code>:
-accessor function for slot <code>bound</code>. </dd>
-<dt>show</dt><dd><code>signature(object = "fiHampel")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>, <code><a href="fiHampel.html">fiHampel</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("fiHampel")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiHampel.html
===================================================================
--- pkg/ROptEst/chm/fiHampel.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiHampel.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,80 +0,0 @@
-<html><head><title>Generating function for fiHampel-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiHampel(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiHampel">
-<param name="keyword" value=" Generating function for fiHampel-class">
-</object>
-
-
-<h2>Generating function for fiHampel-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"fiHampel"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>fiHampel(bound = Inf)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>bound</code></td>
-<td>
-positive real: bias bound </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>fiHampel</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Hampel et al. (1986) <EM>Robust Statistics</EM>.
-The Approach Based on Influence Functions. New York: Wiley.
-</p>
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiHampel-class.html">fiHampel-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-fiHampel()
-
-## The function is currently defined as
-function(bound = Inf){ new("fiHampel", bound = bound) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiMSE-class.html
===================================================================
--- pkg/ROptEst/chm/fiMSE-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiMSE-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-<html><head><title>Finite-sample mean square error</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiMSE-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiMSE-class">
-<param name="keyword" value=" Finite-sample mean square error">
-</object>
-
-
-<h2>Finite-sample mean square error</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of asymptotic mean square error.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("fiMSE", ...)</code>.
-More frequently they are created via the generating function
-<code>fiMSE</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-“finite-sample mean square error”. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"fiRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"fiRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "fiMSE" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>, <code><a href="fiMSE.html">fiMSE</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("fiMSE")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiMSE.html
===================================================================
--- pkg/ROptEst/chm/fiMSE.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiMSE.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,68 +0,0 @@
-<html><head><title>Generating function for fiMSE-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiMSE(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiMSE">
-<param name="keyword" value=" Generating function for fiMSE-class">
-</object>
-
-
-<h2>Generating function for fiMSE-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"fiMSE"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>asMSE()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"fiMSE"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiMSE-class.html">fiMSE-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-fiMSE()
-
-## The function is currently defined as
-function(){ new("fiMSE") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiRisk-class.html
===================================================================
--- pkg/ROptEst/chm/fiRisk-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiRisk-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,75 +0,0 @@
-<html><head><title>Finite-sample risk</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiRisk-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiRisk-class">
-<param name="keyword" value=" Finite-sample risk">
-</object>
-
-
-<h2>Finite-sample risk</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of finite-sample risks.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-A virtual Class: No objects may be created from it.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>.</dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"RiskType"</code>, directly.
-</p>
-
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "fiRisk" in the signature.
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="RiskType-class.html">RiskType-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiUnOvShoot-class.html
===================================================================
--- pkg/ROptEst/chm/fiUnOvShoot-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiUnOvShoot-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,103 +0,0 @@
-<html><head><title>Finite-sample under-/overshoot probability</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiUnOvShoot-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiUnOvShoot-class">
-<param name="keyword" value="R: width,fiUnOvShoot-method">
-<param name="keyword" value="R: show,fiUnOvShoot-method">
-<param name="keyword" value=" Finite-sample under-/overshoot probability">
-</object>
-
-
-<h2>Finite-sample under-/overshoot probability</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of finite-sample under-/overshoot probability.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("fiUnOvShoot", ...)</code>.
-More frequently they are created via the generating function
-<code>fiUnOvShoot</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
-dQuote{finite-sample under-/overshoot probability}. </dd>
-<dt><code>width</code>:</dt><dd>Object of class <code>"numeric"</code>:
-half the width of given confidence interval. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"fiRisk"</code>, directly.<br>
-Class <code>"RiskType"</code>, by class <code>"fiRisk"</code>.
-</p>
-
-
-<h3>Methods</h3>
-
-<dl>
-<dt>width</dt><dd><code>signature(object = "fiUnOvShoot")</code>:
-accessor function for slot <code>width</code>. </dd>
-<dt>show</dt><dd><code>signature(object = "fiUnOvShoot")</code></dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
-Verw. Geb. <B>10</B>:269–278.
-</p>
-<p>
-Rieder, H. (1989) A finite-sample minimax regression estimator.
-Statistics <B>20</B>(2): 211–221.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
-of M-estimators on Neighborhoods.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-new("fiUnOvShoot")
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/fiUnOvShoot.html
===================================================================
--- pkg/ROptEst/chm/fiUnOvShoot.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/fiUnOvShoot.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,88 +0,0 @@
-<html><head><title>Generating function for fiUnOvShoot-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>fiUnOvShoot(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: fiUnOvShoot">
-<param name="keyword" value=" Generating function for fiUnOvShoot-class">
-</object>
-
-
-<h2>Generating function for fiUnOvShoot-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"fiUnOvShoot"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>fiUnOvShoot(width = 1.960)</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>width</code></td>
-<td>
-positive real: half the width of given confidence interval. </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"fiUnOvShoot"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
-Verw. Geb. <B>10</B>:269–278.
-</p>
-<p>
-Rieder, H. (1989) A finite-sample minimax regression estimator.
-Statistics <B>20</B>(2): 211–221.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="fiUnOvShoot-class.html">fiUnOvShoot-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-fiUnOvShoot()
-
-## The function is currently defined as
-function(width = 1.960){ new("fiUnOvShoot", width = width) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/generateIC.html
===================================================================
--- pkg/ROptEst/chm/generateIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/generateIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,78 +0,0 @@
-<html><head><title>Generic function for the generation of influence curves</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>generateIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: generateIC">
-<param name="keyword" value=" Generic function for the generation of influence curves">
-</object>
-
-
-<h2>Generic function for the generation of influence curves</h2>
-
-
-<h3>Description</h3>
-
-<p>
-This function is rarely called directly. It is used
-by other functions to create objects of class <code>"IC"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-generateIC(neighbor, L2Fam, ...)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>neighbor</code></td>
-<td>
-Object of class <code>"Neighborhood"</code>. </td></tr>
-<tr valign="top"><td><code>L2Fam</code></td>
-<td>
-L2-differentiable family of probability measures. </td></tr>
-<tr valign="top"><td><code>...</code></td>
-<td>
-additional parameters </td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"IC"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC-class.html">ContIC-class</a></code>, <code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/getAsRisk.html
===================================================================
--- pkg/ROptEst/chm/getAsRisk.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getAsRisk.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -7,17 +7,18 @@
<table width="100%"><tr><td>getAsRisk(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getAsRisk">
<param name="keyword" value="R: getAsRisk-methods">
-<param name="keyword" value="R: getAsRisk,asMSE,UnivariateDistribution,Neighborhood-method">
-<param name="keyword" value="R: getAsRisk,asMSE,EuclRandVariable,Neighborhood-method">
-<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,ContNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,asBias,RealRandVariable,ContNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,ContNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,asCov,RealRandVariable,ContNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,trAsCov,RealRandVariable,ContNeighborhood-method">
-<param name="keyword" value="R: getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood-method">
+<param name="keyword" value="R: getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method">
+<param name="keyword" value="R: getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method">
<param name="keyword" value=" Generic Function for Computation of Asymptotic Risks">
</object>
@@ -37,52 +38,57 @@
<h3>Usage</h3>
<pre>
-getAsRisk(risk, L2deriv, neighbor, ...)
+getAsRisk(risk, L2deriv, neighbor, biastype, ...)
## S4 method for signature 'asMSE, UnivariateDistribution,
-## Neighborhood':
-getAsRisk(risk, L2deriv, neighbor, clip, cent, stand, trafo)
+## Neighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
## S4 method for signature 'asMSE, EuclRandVariable,
-## Neighborhood':
-getAsRisk(risk, L2deriv, neighbor, clip, cent, stand, trafo)
+## Neighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
## S4 method for signature 'asBias, UnivariateDistribution,
-## ContNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, trafo)
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
## S4 method for signature 'asBias, UnivariateDistribution,
-## TotalVarNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, trafo)
+## TotalVarNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
## S4 method for signature 'asBias, RealRandVariable,
-## ContNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, Distr, L2derivDistrSymm, trafo,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
z.start, A.start, maxiter, tol)
## S4 method for signature 'asCov, UnivariateDistribution,
-## ContNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, clip, cent, stand)
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
## S4 method for signature 'asCov, UnivariateDistribution,
-## TotalVarNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, clip, cent, stand)
+## TotalVarNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
## S4 method for signature 'asCov, RealRandVariable,
-## ContNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, Distr, clip, cent, stand)
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
## S4 method for signature 'trAsCov,
-## UnivariateDistribution, UncondNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, clip, cent, stand)
+## UnivariateDistribution, UncondNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
## S4 method for signature 'trAsCov, RealRandVariable,
-## ContNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, Distr, clip, cent, stand)
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
## S4 method for signature 'asUnOvShoot,
-## UnivariateDistribution, UncondNeighborhood':
-getAsRisk(risk, L2deriv, neighbor, clip, cent, stand, trafo)
+## UnivariateDistribution, UncondNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asSemivar,
+## UnivariateDistribution, Neighborhood, onesidedBias':
+getAsRisk(risk, L2deriv, neighbor, biastype,
+ clip, cent, stand, trafo)
</pre>
@@ -99,6 +105,9 @@
<tr valign="top"><td><code>neighbor</code></td>
<td>
object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
@@ -142,42 +151,46 @@
<h3>Methods</h3>
<dl>
-<dt>risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood":</dt><dd>computes asymptotic mean square error in methods for
+<dt>risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "BiasType":</dt><dd>computes asymptotic mean square error in methods for
function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood":</dt><dd>computes asymptotic mean square error in methods for
+<dt>risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "BiasType":</dt><dd>computes asymptotic mean square error in methods for
function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+<dt>risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood":</dt><dd>computes trace of asymptotic covariance in methods
+<dt>risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":</dt><dd>computes trace of asymptotic covariance in methods
for function <code>getInfRobIC</code>. </dd>
-<dt>risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood":</dt><dd>computes trace of asymptotic covariance in methods for
+<dt>risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes trace of asymptotic covariance in methods for
function <code>getInfRobIC</code>. </dd>
-<dt>risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood":</dt><dd>computes asymptotic under-/overshoot risk in methods for
+<dt>risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic under-/overshoot risk in methods for
function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asSemivar", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "onesidedBias":</dt><dd>computes asymptotic semivariance in methods for
+function <code>getInfRobIC</code>. </dd>
</dl>
<h3>Author(s)</h3>
@@ -205,11 +218,20 @@
<h3>See Also</h3>
<p>
-<code><a href="asRisk-class.html">asRisk-class</a></code>
+<code><a onclick="findlink('distrMod', 'asRisk-class.html')" style="text-decoration: underline; color: blue; cursor: hand">asRisk-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Added: pkg/ROptEst/chm/getBiasIC.html
===================================================================
--- pkg/ROptEst/chm/getBiasIC.html (rev 0)
+++ pkg/ROptEst/chm/getBiasIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,166 @@
+<html><head><title>Generic function for the computation of the asymptotic bias for an IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>getBiasIC(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: getBiasIC">
+<param name="keyword" value="R: getBiasIC-methods">
+<param name="keyword" value="R: getBiasIC,IC,ContNeighborhood,missing,BiasType-method">
+<param name="keyword" value="R: getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method">
+<param name="keyword" value="R: getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method">
+<param name="keyword" value="R: getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method">
+<param name="keyword" value=" Generic function for the computation of the asymptotic bias for an IC">
+</object>
+
+
+<h2>Generic function for the computation of the asymptotic bias for an IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the asymptotic bias for an IC.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getBiasIC(IC, neighbor, L2Fam, biastype, ...)
+
+## S4 method for signature 'IC, ContNeighborhood, missing,
+## BiasType':
+getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, ContNeighborhood,
+## L2ParamFamily, BiasType':
+getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, TotalVarNeighborhood,
+## missing, BiasType':
+getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, TotalVarNeighborhood,
+## L2ParamFamily, BiasType':
+getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+To make sure that the results are valid, it is recommended
+to include an additional check of the IC properties of <code>IC</code>
+using <code>checkIC</code>.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The asymptotic bias of an IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+</p>
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> in case of convex contamination neighborhoods
+and symmetric bias. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code>
+in case of convex contamination neighborhoods and symmetric bias. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> in case of total variation neighborhoods
+and symmetric bias. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code>
+in case of total variation neighborhoods and symmetric bias. </dd>
+</dl>
+
+<h3>Note</h3>
+
+<p>
+This generic function is still under construction.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/ROptEst/chm/getFiRisk.html
===================================================================
--- pkg/ROptEst/chm/getFiRisk.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getFiRisk.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -32,13 +32,13 @@
## S4 method for signature 'fiUnOvShoot, Norm,
## ContNeighborhood':
-getFiRisk(risk, Distr, neighbor,
- clip, stand, sampleSize, Algo, cont)
+getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
## S4 method for signature 'fiUnOvShoot, Norm,
## TotalVarNeighborhood':
-getFiRisk(risk, Distr, neighbor,
- clip, stand, sampleSize, Algo, cont)
+getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
</pre>
@@ -124,11 +124,20 @@
<h3>See Also</h3>
<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>
+<code><a onclick="findlink('distrMod', 'fiRisk-class.html')" style="text-decoration: underline; color: blue; cursor: hand">fiRisk-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getFixClip.html
===================================================================
--- pkg/ROptEst/chm/getFixClip.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getFixClip.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -28,7 +28,7 @@
<h3>Usage</h3>
<pre>
-getFixClip(clip, Distr, risk, neighbor, ...)
+getFixClip(clip, Distr, risk, neighbor, ...)
## S4 method for signature 'numeric, Norm, fiUnOvShoot,
## ContNeighborhood':
@@ -96,11 +96,20 @@
<h3>See Also</h3>
<p>
-<code><a href="ContIC-class.html">ContIC-class</a></code>, <code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a onclick="findlink('RobAStBase', 'TotalVarIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">TotalVarIC-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getFixRobIC.html
===================================================================
--- pkg/ROptEst/chm/getFixRobIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getFixRobIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -32,7 +32,7 @@
## S4 method for signature 'Norm, fiUnOvShoot,
## UncondNeighborhood':
getFixRobIC(Distr, risk, neighbor,
- sampleSize, upper, maxiter, tol, warn, Algo, cont)
+ sampleSize, upper, maxiter, tol, warn, Algo, cont)
</pre>
@@ -108,11 +108,20 @@
<h3>See Also</h3>
<p>
-<code><a href="FixRobModel-class.html">FixRobModel-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'FixRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">FixRobModel-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getIneffDiff.html
===================================================================
--- pkg/ROptEst/chm/getIneffDiff.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getIneffDiff.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -7,7 +7,7 @@
<table width="100%"><tr><td>getIneffDiff(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getIneffDiff">
<param name="keyword" value="R: getIneffDiff-methods">
-<param name="keyword" value="R: getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE-method">
+<param name="keyword" value="R: getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method">
<param name="keyword" value=" Generic Function for the Computation of Inefficiency Differences">
</object>
@@ -27,11 +27,12 @@
<h3>Usage</h3>
<pre>
-getIneffDiff(radius, L2Fam, neighbor, risk, ...)
+getIneffDiff(radius, L2Fam, neighbor, risk, biastype, ...)
## S4 method for signature 'numeric, L2ParamFamily,
-## UncondNeighborhood, asMSE':
-getIneffDiff(radius, L2Fam, neighbor, risk, loRad, upRad,
+## UncondNeighborhood, asMSE, BiasType':
+getIneffDiff(
+ radius, L2Fam, neighbor, risk, biastype = symmetricBias(), loRad, upRad,
loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
</pre>
@@ -51,6 +52,9 @@
<tr valign="top"><td><code>risk</code></td>
<td>
object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
@@ -96,14 +100,15 @@
<dl>
<dt>radius = "numeric", L2Fam = "L2ParamFamily",
-neighbor = "UncondNeighborhood", risk = "asMSE":</dt><dd>computes difference of asymptotic MSE–inefficiency for
+neighbor = "UncondNeighborhood", risk = "asMSE", biastype = "BiasType":</dt><dd>computes difference of asymptotic MSE–inefficiency for
the boundaries of a given radius interval.</dd>
</dl>
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -117,6 +122,10 @@
<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
</p>
<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -130,6 +139,6 @@
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getInfCent.html
===================================================================
--- pkg/ROptEst/chm/getInfCent.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getInfCent.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -7,9 +7,11 @@
<table width="100%"><tr><td>getInfCent(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getInfCent">
<param name="keyword" value="R: getInfCent-methods">
-<param name="keyword" value="R: getInfCent,UnivariateDistribution,ContNeighborhood-method">
-<param name="keyword" value="R: getInfCent,UnivariateDistribution,TotalVarNeighborhood-method">
-<param name="keyword" value="R: getInfCent,RealRandVariable,ContNeighborhood-method">
+<param name="keyword" value="R: getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfCent,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
+<param name="keyword" value="R: getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
<param name="keyword" value=" Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound">
</object>
@@ -31,19 +33,32 @@
<h3>Usage</h3>
<pre>
-getInfCent(L2deriv, neighbor, ...)
+getInfCent(L2deriv, neighbor, biastype, ...)
## S4 method for signature 'UnivariateDistribution,
-## ContNeighborhood':
-getInfCent(L2deriv, neighbor, clip, cent, tol.z, symm, trafo)
+## ContNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
## S4 method for signature 'UnivariateDistribution,
-## TotalVarNeighborhood':
-getInfCent(L2deriv, neighbor, clip, cent, tol.z, symm, trafo)
+## TotalVarNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
## S4 method for signature 'RealRandVariable,
-## ContNeighborhood':
-getInfCent(L2deriv, neighbor, z.comp, stand, cent, clip)
+## ContNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, onesidedBias':
+getInfCent(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+getInfCent(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
</pre>
@@ -57,6 +72,9 @@
<tr valign="top"><td><code>neighbor</code></td>
<td>
object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
@@ -92,19 +110,26 @@
<h3>Methods</h3>
<dl>
-<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood"</dt><dd>computation of optimal centering constant. </dd>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType"</dt><dd>computation of optimal centering constant for symmetric bias. </dd>
-<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood"</dt><dd>computation of optimal lower clipping bound. </dd>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType"</dt><dd>computation of optimal lower clipping bound for symmetric bias. </dd>
-<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood"</dt><dd>computation of optimal centering constant. </dd>
+<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType"</dt><dd>computation of optimal centering constant for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias"</dt><dd>computation of optimal centering constant for onesided bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias"</dt><dd>computation of optimal centering constant for asymmetric bias. </dd>
</dl>
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -114,6 +139,10 @@
Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
</p>
<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -122,11 +151,20 @@
<h3>See Also</h3>
<p>
-<code><a href="ContIC-class.html">ContIC-class</a></code>, <code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a onclick="findlink('RobAStBase', 'TotalVarIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">TotalVarIC-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getInfClip.html
===================================================================
--- pkg/ROptEst/chm/getInfClip.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getInfClip.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -11,6 +11,7 @@
<param name="keyword" value="R: getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method">
<param name="keyword" value="R: getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood-method">
<param name="keyword" value="R: getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method">
+<param name="keyword" value="R: getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method">
<param name="keyword" value=" Generic Function for the Computation of the Optimal Clipping Bound">
</object>
@@ -34,20 +35,24 @@
## S4 method for signature 'numeric,
## UnivariateDistribution, asMSE, ContNeighborhood':
-getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature 'numeric,
## UnivariateDistribution, asMSE, TotalVarNeighborhood':
-getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature 'numeric, EuclRandVariable,
## asMSE, ContNeighborhood':
-getInfClip(clip, L2deriv, risk, neighbor, Distr, stand, cent, trafo)
+getInfClip(clip, L2deriv, risk, neighbor, Distr, stand, biastype, cent, trafo)
## S4 method for signature 'numeric,
## UnivariateDistribution, asUnOvShoot,
## UncondNeighborhood':
-getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asSemivar, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
</pre>
@@ -70,6 +75,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
<tr valign="top"><td><code>cent</code></td>
<td>
optimal centering constant. </td></tr>
@@ -109,12 +117,17 @@
<dt>clip = "numeric", L2deriv = "UnivariateDistribution",
risk = "asUnOvShoot", neighbor = "UncondNeighborhood"</dt><dd>optimal clipping bound for asymtotic under-/overshoot risk. </dd>
+
+
+<dt>clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asSemivar", neighbor = "ContNeighborhood"</dt><dd>optimal clipping bound for asymtotic semivariance.</dd>
</dl>
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -127,6 +140,10 @@
Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
</p>
<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -135,11 +152,20 @@
<h3>See Also</h3>
<p>
-<code><a href="ContIC-class.html">ContIC-class</a></code>, <code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a onclick="findlink('RobAStBase', 'TotalVarIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">TotalVarIC-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getInfGamma.html
===================================================================
--- pkg/ROptEst/chm/getInfGamma.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getInfGamma.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -7,10 +7,12 @@
<table width="100%"><tr><td>getInfGamma(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getInfGamma">
<param name="keyword" value="R: getInfGamma-methods">
-<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood-method">
-<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood-method">
-<param name="keyword" value="R: getInfGamma,RealRandVariable,asMSE,ContNeighborhood-method">
-<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood-method">
+<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method">
+<param name="keyword" value="R: getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method">
<param name="keyword" value=" Generic Function for the Computation of the Optimal Clipping Bound">
</object>
@@ -30,23 +32,37 @@
<h3>Usage</h3>
<pre>
-getInfGamma(L2deriv, risk, neighbor, ...)
+getInfGamma(L2deriv, risk, neighbor, biastype, ...)
## S4 method for signature 'UnivariateDistribution, asMSE,
-## ContNeighborhood':
-getInfGamma(L2deriv, risk, neighbor, cent, clip)
+## ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
## S4 method for signature 'UnivariateDistribution,
-## asGRisk, TotalVarNeighborhood':
-getInfGamma(L2deriv, risk, neighbor, cent, clip)
+## asGRisk, TotalVarNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
## S4 method for signature 'RealRandVariable, asMSE,
-## ContNeighborhood':
-getInfGamma(L2deriv, risk, neighbor, Distr, stand, cent, clip)
+## ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
## S4 method for signature 'UnivariateDistribution,
-## asUnOvShoot, ContNeighborhood':
-getInfGamma(L2deriv, risk, neighbor, cent, clip)
+## asUnOvShoot, ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, onesidedBias':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = positiveBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, asymmetricBias':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = asymmetricBias(), cent, clip)
</pre>
@@ -63,6 +79,9 @@
<tr valign="top"><td><code>neighbor</code></td>
<td>
object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
@@ -92,25 +111,40 @@
<dl>
<dt>L2deriv = "UnivariateDistribution", risk = "asMSE",
-neighbor = "ContNeighborhood"</dt><dd>used by <code>getInfClip</code>. </dd>
+neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
<dt>L2deriv = "UnivariateDistribution", risk = "asGRisk",
-neighbor = "TotalVarNeighborhood"</dt><dd>used by <code>getInfClip</code>. </dd>
+neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
<dt>L2deriv = "RealRandVariable", risk = "asMSE",
-neighbor = "ContNeighborhood"</dt><dd>used by <code>getInfClip</code>. </dd>
+neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
<dt>L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",
-neighbor = "ContNeighborhood"</dt><dd>used by <code>getInfClip</code>. </dd>
+neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "onesidedBias"</dt><dd>used by <code>getInfClip</code> for onesided bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"</dt><dd>used by <code>getInfClip</code> for asymmetric bias. </dd>
</dl>
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -124,9 +158,13 @@
</p>
<p>
Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
-General Loss Functions. Statistics & Decisions (submitted).
+General Loss Functions. Statistics & Decisions <EM>22</EM>, 201-223.
</p>
<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -135,13 +173,22 @@
<h3>See Also</h3>
<p>
-<code><a href="asGRisk-class.html">asGRisk-class</a></code>, <code><a href="asMSE-class.html">asMSE-class</a></code>,
-<code><a href="asUnOvShoot-class.html">asUnOvShoot-class</a></code>, <code><a href="ContIC-class.html">ContIC-class</a></code>,
-<code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
+<code><a onclick="findlink('distrMod', 'asGRisk-class.html')" style="text-decoration: underline; color: blue; cursor: hand">asGRisk-class</a></code>, <code><a onclick="findlink('distrMod', 'asMSE-class.html')" style="text-decoration: underline; color: blue; cursor: hand">asMSE-class</a></code>,
+<code><a onclick="findlink('distrMod', 'asUnOvShoot-class.html')" style="text-decoration: underline; color: blue; cursor: hand">asUnOvShoot-class</a></code>, <code><a onclick="findlink('RobAStBase', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>,
+<code><a onclick="findlink('RobAStBase', 'TotalVarIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">TotalVarIC-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getInfRobIC.html
===================================================================
--- pkg/ROptEst/chm/getInfRobIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getInfRobIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -10,8 +10,7 @@
<param name="keyword" value="R: getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method">
<param name="keyword" value="R: getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method">
<param name="keyword" value="R: getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method">
-<param name="keyword" value="R: getInfRobIC,UnivariateDistribution,asBias,ContNeighborhood-method">
-<param name="keyword" value="R: getInfRobIC,UnivariateDistribution,asBias,TotalVarNeighborhood-method">
+<param name="keyword" value="R: getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method">
<param name="keyword" value="R: getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method">
<param name="keyword" value="R: getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method">
<param name="keyword" value="R: getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method">
@@ -52,15 +51,10 @@
getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo)
## S4 method for signature 'UnivariateDistribution, asBias,
-## ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
+## UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
-## S4 method for signature 'UnivariateDistribution, asBias,
-## TotalVarNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
- upper, maxiter, tol, warn)
-
## S4 method for signature 'RealRandVariable, asBias,
## ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
@@ -68,27 +62,27 @@
## S4 method for signature 'UnivariateDistribution,
## asHampel, UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable, asHampel,
## ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,
## asGRisk, UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
## S4 method for signature 'RealRandVariable, asGRisk,
## ContNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
## S4 method for signature 'UnivariateDistribution,
## asUnOvShoot, UncondNeighborhood':
-getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo,
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
</pre>
@@ -109,6 +103,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
<tr valign="top"><td><code>Distr</code></td>
<td>
object of class <code>"Distribution"</code>. </td></tr>
@@ -175,15 +172,10 @@
<dt>L2deriv = "UnivariateDistribution", risk = "asBias",
-neighbor = "ContNeighborhood"</dt><dd>computes the bias optimal influence curve for L2 differentiable
+neighbor = "UncondNeighborhood"</dt><dd>computes the bias optimal influence curve for L2 differentiable
parametric families with unknown one-dimensional parameter. </dd>
-<dt>L2deriv = "UnivariateDistribution", risk = "asBias",
-neighbor = "TotalVarNeighborhood"</dt><dd>computes the bias optimal influence curve for L2 differentiable
-parametric families with unknown one-dimensional parameter. </dd>
-
-
<dt>L2deriv = "RealRandVariable", risk = "asBias",
neighbor = "ContNeighborhood"</dt><dd>computes the bias optimal influence curve for L2 differentiable
parametric families with unknown <i>k</i>-dimensional parameter
@@ -228,12 +220,20 @@
<h3>References</h3>
<p>
-Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106-115.
</p>
<p>
Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
</p>
<p>
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics & Decisions <B>22</B>: 201-223.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -242,11 +242,20 @@
<h3>See Also</h3>
<p>
-<code><a href="InfRobModel-class.html">InfRobModel-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/getInfStand.html
===================================================================
--- pkg/ROptEst/chm/getInfStand.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getInfStand.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -7,9 +7,11 @@
<table width="100%"><tr><td>getInfStand(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: getInfStand">
<param name="keyword" value="R: getInfStand-methods">
-<param name="keyword" value="R: getInfStand,UnivariateDistribution,ContNeighborhood-method">
-<param name="keyword" value="R: getInfStand,UnivariateDistribution,TotalVarNeighborhood-method">
-<param name="keyword" value="R: getInfStand,RealRandVariable,ContNeighborhood-method">
+<param name="keyword" value="R: getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfStand,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method">
+<param name="keyword" value="R: getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
<param name="keyword" value=" Generic Function for the Computation of the Standardizing Matrix">
</object>
@@ -29,19 +31,32 @@
<h3>Usage</h3>
<pre>
-getInfStand(L2deriv, neighbor, ...)
+getInfStand(L2deriv, neighbor, biastype, ...)
## S4 method for signature 'UnivariateDistribution,
-## ContNeighborhood':
-getInfStand(L2deriv, neighbor, clip, cent, trafo)
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
## S4 method for signature 'UnivariateDistribution,
-## TotalVarNeighborhood':
-getInfStand(L2deriv, neighbor, clip, cent, trafo)
+## TotalVarNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+
## S4 method for signature 'UnivariateDistribution,
-## ContNeighborhood':
-getInfStand(L2deriv, neighbor, Distr, A.comp, stand, clip, cent, trafo)
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, trafo)
</pre>
@@ -55,6 +70,9 @@
<tr valign="top"><td><code>neighbor</code></td>
<td>
object of class <code>"Neighborhood"</code> </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
@@ -87,19 +105,31 @@
<h3>Methods</h3>
<dl>
-<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood"</dt><dd>computes standardizing matrix. </dd>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes standardizing matrix for symmetric bias. </dd>
-<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood"</dt><dd>computes standardizing matrix. </dd>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"</dt><dd>computes standardizing matrix for symmetric bias. </dd>
-<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood"</dt><dd>computes standardizing matrix. </dd>
+<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes standardizing matrix for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "onesidedBias"</dt><dd>computes standardizing matrix for onesided bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"</dt><dd>computes standardizing matrix for asymmetric bias. </dd>
</dl>
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -109,6 +139,10 @@
Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
</p>
<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -117,11 +151,20 @@
<h3>See Also</h3>
<p>
-<code><a href="ContIC-class.html">ContIC-class</a></code>, <code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a onclick="findlink('RobAStBase', 'TotalVarIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">TotalVarIC-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Added: pkg/ROptEst/chm/getL1normL2deriv.html
===================================================================
--- pkg/ROptEst/chm/getL1normL2deriv.html (rev 0)
+++ pkg/ROptEst/chm/getL1normL2deriv.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,82 @@
+<html><head><title>Calculation of L1 norm of L2derivative</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>getL1normL2deriv(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: getL1normL2deriv">
+<param name="keyword" value="R: getL1normL2deriv-methods">
+<param name="keyword" value="R: getL1normL2deriv,UnivariateDistribution-method">
+<param name="keyword" value="R: getL1normL2deriv,RealRandVariable-method">
+<param name="keyword" value=" Calculation of L1 norm of L2derivative">
+</object>
+
+
+<h2>Calculation of L1 norm of L2derivative</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Methods to calculate the L1 norm of the L2derivative in a smooth parametric model.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>getL1normL2deriv(L2deriv, ...)
+## S4 method for signature 'UnivariateDistribution':
+getL1normL2deriv(L2deriv,
+ cent, ...)
+
+## S4 method for signature 'UnivariateDistribution':
+getL1normL2deriv(L2deriv,
+ cent, stand, Distr, ...)
+
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2derivative of the model</td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+centering Lagrange Multiplier</td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing Lagrange Multiplier</td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+distribution of the L2derivative</td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+further arguments (not used at the moment)</td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+L1 norm of the L2derivative</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+##
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst/chm/getL2normL2deriv.html
===================================================================
--- pkg/ROptEst/chm/getL2normL2deriv.html (rev 0)
+++ pkg/ROptEst/chm/getL2normL2deriv.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,64 @@
+<html><head><title>Calculation of L2 norm of L2derivative</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>getL2normL2deriv(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: getL2normL2deriv">
+<param name="keyword" value=" Calculation of L2 norm of L2derivative">
+</object>
+
+
+<h2>Calculation of L2 norm of L2derivative</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Function to calculate the L2 norm of the L2derivative in a smooth parametric model.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>getL2normL2deriv(aFinfo, cent, ...)</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>aFinfo</code></td>
+<td>
+trace of the Fisher information</td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+centering</td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+further arguments (not used at the moment)</td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+L2 norm of the L2derivative</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+##
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/ROptEst/chm/getRiskIC.html
===================================================================
--- pkg/ROptEst/chm/getRiskIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/getRiskIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -11,10 +11,8 @@
<param name="keyword" value="R: getRiskIC,IC,asCov,missing,L2ParamFamily-method">
<param name="keyword" value="R: getRiskIC,IC,trAsCov,missing,missing-method">
<param name="keyword" value="R: getRiskIC,IC,trAsCov,missing,L2ParamFamily-method">
-<param name="keyword" value="R: getRiskIC,IC,asBias,ContNeighborhood,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,asBias,ContNeighborhood,L2ParamFamily-method">
-<param name="keyword" value="R: getRiskIC,IC,asBias,TotalVarNeighborhood,missing-method">
-<param name="keyword" value="R: getRiskIC,IC,asBias,TotalVarNeighborhood,L2ParamFamily-method">
+<param name="keyword" value="R: getRiskIC,IC,asBias,UncondNeighborhood,missing-method">
+<param name="keyword" value="R: getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method">
<param name="keyword" value="R: getRiskIC,IC,asMSE,UncondNeighborhood,missing-method">
<param name="keyword" value="R: getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method">
<param name="keyword" value="R: getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method">
@@ -53,29 +51,21 @@
## L2ParamFamily':
getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
-## S4 method for signature 'IC, asBias, ContNeighborhood,
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
## missing':
-getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
-## S4 method for signature 'IC, asBias, ContNeighborhood,
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
## L2ParamFamily':
-getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
-## S4 method for signature 'IC, asBias,
-## TotalVarNeighborhood, missing':
-getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
-
-## S4 method for signature 'IC, asBias,
-## TotalVarNeighborhood, L2ParamFamily':
-getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
-
## S4 method for signature 'IC, asMSE, UncondNeighborhood,
## missing':
-getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
## S4 method for signature 'IC, asMSE, UncondNeighborhood,
## L2ParamFamily':
-getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
## S4 method for signature 'TotalVarIC, asUnOvShoot,
## UncondNeighborhood, missing':
@@ -109,6 +99,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
<tr valign="top"><td><code>tol</code></td>
<td>
the desired accuracy (convergence tolerance).</td></tr>
@@ -219,11 +212,20 @@
<h3>See Also</h3>
<p>
-<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a href="InfRobModel-class.html">InfRobModel-class</a></code>
+<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Deleted: pkg/ROptEst/chm/infoPlot.html
===================================================================
--- pkg/ROptEst/chm/infoPlot.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/infoPlot.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Plot absolute and relative information</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>infoPlot(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: infoPlot">
-<param name="keyword" value=" Plot absolute and relative information">
-</object>
-
-
-<h2>Plot absolute and relative information</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Plot absolute and relative information of influence curves.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-infoPlot(object)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>object</code></td>
-<td>
-object of class <code>"InfluenceCurve"</code> </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-Absolute information is defined as the square of the length
-of an IC. The relative information is defined as the
-absolute information of one component with respect to the
-absolute information of the whole IC; confer Section 8.1
-of Kohl (2005).
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a href="IC-class.html">IC-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-N <- NormLocationScaleFamily(mean=0, sd=1)
-IC1 <- optIC(model = N, risk = asCov())
-infoPlot(IC1)
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/ksEstimator.html
===================================================================
--- pkg/ROptEst/chm/ksEstimator.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/ksEstimator.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,172 +0,0 @@
-<html><head><title>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>ksEstimator(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: ksEstimator">
-<param name="keyword" value="R: ksEstimator-methods">
-<param name="keyword" value="R: ksEstimator,numeric,Binom-method">
-<param name="keyword" value="R: ksEstimator,numeric,Pois-method">
-<param name="keyword" value="R: ksEstimator,numeric,Norm-method">
-<param name="keyword" value="R: ksEstimator,numeric,Lnorm-method">
-<param name="keyword" value="R: ksEstimator,numeric,Gumbel-method">
-<param name="keyword" value="R: ksEstimator,numeric,Exp-method">
-<param name="keyword" value="R: ksEstimator,numeric,Gammad-method">
-<param name="keyword" value=" Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator">
-</object>
-
-
-<h2>Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generic function for the computation of the Kolmogorov(-Smirnov)
-minimum distance estimator.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-ksEstimator(x, distribution, ...)
-
-## S4 method for signature 'numeric, Binom':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-## S4 method for signature 'numeric, Pois':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-## S4 method for signature 'numeric, Norm':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-## S4 method for signature 'numeric, Lnorm':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-## S4 method for signature 'numeric, Gumbel':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-## S4 method for signature 'numeric, Exp':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-## S4 method for signature 'numeric, Gammad':
-ksEstimator(x, distribution, param, eps = .Machine$double.eps^0.5)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>x</code></td>
-<td>
-sample </td></tr>
-<tr valign="top"><td><code>distribution</code></td>
-<td>
-object of class <code>"Distribution"</code> </td></tr>
-<tr valign="top"><td><code>...</code></td>
-<td>
-additional parameters </td></tr>
-<tr valign="top"><td><code>param</code></td>
-<td>
-name of the unknown parameter. If missing all parameters
-of the corresponding distribution are estimated. </td></tr>
-<tr valign="top"><td><code>eps</code></td>
-<td>
-the desired accuracy (convergence tolerance). </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-In case of discrete distributions the Kolmogorov distance is computed and
-the parameters which lead to the minimum distance are returned. In case of
-absolutely continuous distributions <code>ks.test</code> is called and the parameters
-which minimize the corresponding test statistic are returned.
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-The Kolmogorov minimum distance estimator is computed. Returns a list
-with components named like the parameters of <code>distribution</code>.</p>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>x = "numeric", distribution = "Binom"</dt><dd>Binomial distributions. </dd>
-
-
-<dt>x = "numeric", distribution = "Pois"</dt><dd>Poisson distributions. </dd>
-
-
-<dt>x = "numeric", distribution = "Norm"</dt><dd>Normal distributions. </dd>
-
-
-<dt>x = "numeric", distribution = "Lnorm"</dt><dd>Lognormal distributions. </dd>
-
-
-<dt>x = "numeric", distribution = "Gumbel"</dt><dd>Gumbel distributions. </dd>
-
-
-<dt>x = "numeric", distribution = "Exp"</dt><dd>Exponential distributions. </dd>
-
-
-<dt>x = "numeric", distribution = "Gamma"</dt><dd>Gamma distributions. </dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a onclick="findlink('distr', 'Distribution-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Distribution-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-x <- rnorm(100, mean = 1, sd = 2)
-ksEstimator(x=x, distribution = Norm()) # estimate mean and sd
-ksEstimator(x=x, distribution = Norm(mean = 1), param = "sd") # estimate sd
-ksEstimator(x=x, distribution = Norm(sd = 2), param = "mean") # estimate mean
-mean(x)
-median(x)
-sd(x)
-mad(x)
-</pre>
-
-<script Language="JScript">
-function findlink(pkg, fn) {
-var Y, link;
-Y = location.href.lastIndexOf("\\") + 1;
-link = location.href.substring(0, Y);
-link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
-location.href = link;
-}
-</script>
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/leastFavorableRadius.html
===================================================================
--- pkg/ROptEst/chm/leastFavorableRadius.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/leastFavorableRadius.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -29,7 +29,8 @@
## S4 method for signature 'L2ParamFamily,
## UncondNeighborhood, asGRisk':
-leastFavorableRadius(L2Fam, neighbor, risk, rho, upRad = 1,
+leastFavorableRadius(
+ L2Fam, neighbor, risk, biastype = symmetricBias(), rho, upRad = 1,
z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
tol = .Machine$double.eps^0.4, warn = FALSE)
</pre>
@@ -50,6 +51,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
<tr valign="top"><td><code>upRad</code></td>
<td>
the upper end point of the radius interval to be searched. </td></tr>
@@ -93,13 +97,18 @@
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
<h3>References</h3>
<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+the Radius. Statistical Methods and Applications <EM>17</EM>(1) 13-40.
+</p>
+<p>
Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
the Radius. Submitted. Appeared as discussion paper Nr. 81.
SFB 373 (Quantification and Simulation of Economic Processes),
@@ -107,6 +116,10 @@
<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
</p>
<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
@@ -129,6 +142,6 @@
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/locMEstimator.html
===================================================================
--- pkg/ROptEst/chm/locMEstimator.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/locMEstimator.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -91,11 +91,20 @@
<h3>See Also</h3>
<p>
-<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'InfluenceCurve-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfluenceCurve-class</a></code>
</p>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/lowerCaseRadius.html
===================================================================
--- pkg/ROptEst/chm/lowerCaseRadius.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/lowerCaseRadius.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -7,8 +7,8 @@
<table width="100%"><tr><td>lowerCaseRadius(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
<param name="keyword" value="R: lowerCaseRadius">
<param name="keyword" value="R: lowerCaseRadius-methods">
-<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE-method">
-<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE-method">
+<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method">
+<param name="keyword" value="R: lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method">
<param name="keyword" value=" Computation of the lower case radius">
</object>
@@ -20,14 +20,14 @@
<p>
The lower case radius is computed; confer Subsection 2.1.2
-in Kohl (2005).
+in Kohl (2005) and formula (4.5) in Ruckdeschel (2005).
</p>
<h3>Usage</h3>
<pre>
-lowerCaseRadius(L2Fam, neighbor, risk, ...)
+lowerCaseRadius(L2Fam, neighbor, risk, biastype, ...)
</pre>
@@ -43,6 +43,9 @@
<tr valign="top"><td><code>risk</code></td>
<td>
object of class <code>"RiskType"</code> </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
@@ -56,16 +59,21 @@
<h3>Methods</h3>
<dl>
-<dt>L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"ContNeighborhood"</code>.</dd>
+<dt>L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE",
+biastype = "BiasType"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"ContNeighborhood"</code>
+for symmetric bias.</dd>
-<dt>L2Fam = "L2ParamFamily", neighbor = "TotalVarNeighborhood", risk = "asMSE"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"TotalVarNeighborhood"</code>.</dd>
+<dt>L2Fam = "L2ParamFamily", neighbor = "TotalVarNeighborhood", risk = "asMSE",
+biastype = "BiasType"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"TotalVarNeighborhood"</code>;
+(argument biastype is just for signature reasons).</dd>
</dl>
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -75,12 +83,16 @@
Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
Bayreuth: Dissertation.
</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
<h3>See Also</h3>
<p>
-<code><a href="L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a href="Neighborhood-class.html">Neighborhood-class</a></code>
+<code><a onclick="findlink('distrMod', 'L2ParamFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">L2ParamFamily-class</a></code>, <code><a onclick="findlink('RobAStBase', 'Neighborhood-class.html')" style="text-decoration: underline; color: blue; cursor: hand">Neighborhood-class</a></code>
</p>
@@ -91,8 +103,17 @@
lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
</pre>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Added: pkg/ROptEst/chm/minmaxBias.html
===================================================================
--- pkg/ROptEst/chm/minmaxBias.html (rev 0)
+++ pkg/ROptEst/chm/minmaxBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,191 @@
+<html><head><title>Generic Function for the Computation of Bias-Optimally Robust ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>minmaxBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: minmaxBias">
+<param name="keyword" value="R: minmaxBias-methods">
+<param name="keyword" value="R: minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method">
+<param name="keyword" value="R: minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method">
+<param name="keyword" value="R: minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method">
+<param name="keyword" value="R: minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method">
+<param name="keyword" value=" Generic Function for the Computation of Bias-Optimally Robust ICs">
+</object>
+
+
+<h2>Generic Function for the Computation of Bias-Optimally Robust ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of bias-optimally robust ICs
+in case of infinitesimal robust models. This function is
+rarely called directly.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+minmaxBias(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+minmaxBias(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>symm</code></td>
+<td>
+logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
+<tr valign="top"><td><code>DistrSymm</code></td>
+<td>
+object of class <code>"DistributionSymmetry"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivSymm</code></td>
+<td>
+object of class <code>"FunSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivDistrSymm</code></td>
+<td>
+object of class <code>"DistrSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>Finfo</code></td>
+<td>
+Fisher information matrix. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The bias-optimally robust IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"</dt><dd>computes the bias optimal influence curve for asymmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown <i>k</i>-dimensional parameter
+(<i>k > 1</i>) where the underlying distribution is univariate. </dd>
+
+<p>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('RobAStBase', 'InfRobModel-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfRobModel-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Deleted: pkg/ROptEst/chm/negativeBias.html
===================================================================
--- pkg/ROptEst/chm/negativeBias.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/negativeBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Generating function for onesidedBiasType-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>negativeBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: negativeBias">
-<param name="keyword" value=" Generating function for onesidedBiasType-class">
-</object>
-
-
-<h2>Generating function for onesidedBiasType-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"onesidedBiasType"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>negativeBias(name = "negative Bias")</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-name of the bias type</td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"onesidedBiasType"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="onesidedBiasType-class.html">onesidedBiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-negativeBias()
-
-## The function is currently defined as
-function(){ new("onesidedBiasType", name = "negative Bias", sign = -1) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/oneStepEstimator.html
===================================================================
--- pkg/ROptEst/chm/oneStepEstimator.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/oneStepEstimator.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,100 +0,0 @@
-<html><head><title>Generic function for the computation of one-step estimators</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>oneStepEstimator(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: oneStepEstimator">
-<param name="keyword" value="R: oneStepEstimator-methods">
-<param name="keyword" value="R: oneStepEstimator,numeric,InfluenceCurve,numeric-method">
-<param name="keyword" value="R: oneStepEstimator,numeric,InfluenceCurve,list-method">
-<param name="keyword" value="R: oneStepEstimator,matrix,InfluenceCurve,numeric-method">
-<param name="keyword" value="R: oneStepEstimator,matrix,InfluenceCurve,list-method">
-<param name="keyword" value=" Generic function for the computation of one-step estimators">
-</object>
-
-
-<h2>Generic function for the computation of one-step estimators</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generic function for the computation of one-step estimators.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>
-oneStepEstimator(x, IC, start)
-</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>x</code></td>
-<td>
-sample </td></tr>
-<tr valign="top"><td><code>IC</code></td>
-<td>
-object of class <code>"InfluenceCurve"</code> </td></tr>
-<tr valign="top"><td><code>start</code></td>
-<td>
-initial estimate </td></tr>
-</table>
-
-<h3>Details</h3>
-
-<p>
-Given an initial estimation <code>start</code>, a sample <code>x</code>
-and an influence curve <code>IC</code> the corresponding one-step
-estimator is computed
-</p>
-
-
-<h3>Value</h3>
-
-<p>
-The one-step estimation is computed.</p>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>x = "numeric", IC = "InfluenceCurve", start = "numeric"</dt><dd>univariate samples. </dd>
-<dt>x = "numeric", IC = "InfluenceCurve", start = "list"</dt><dd>univariate samples. </dd>
-<dt>x = "matrix", IC = "InfluenceCurve", start = "numeric"</dt><dd>multivariate samples. </dd>
-<dt>x = "matrix", IC = "InfluenceCurve", start = "list"</dt><dd>multivariate samples. </dd>
-</dl>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>
-</p>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/onesidedBiasType-class.html
===================================================================
--- pkg/ROptEst/chm/onesidedBiasType-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/onesidedBiasType-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,110 +0,0 @@
-<html><head><title>onesided Bias Type</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>onesidedBiasType-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: onesidedBiasType-class">
-<param name="keyword" value="R: sign">
-<param name="keyword" value="R: sign<-">
-<param name="keyword" value="R: sign,onesidedBiasType-method">
-<param name="keyword" value="R: sign<-,onesidedBiasType-method">
-<param name="keyword" value=" onesided Bias Type">
-</object>
-
-
-<h2>onesided Bias Type</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of onesided bias types.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("onesidedBiasType", ...)</code>.
-More frequently they are created via the generating function
-<code>positiveBias</code> or <code>negativeBias</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>.</dd>
-<dt><code>sign</code>:</dt><dd>Object of class <code>"numeric"</code>;
-to be {-1,1} — whether bias is to be positive or negative</dd>
-</dl>
-
-<h3>Methods</h3>
-
-<dl>
-<dt>sign</dt><dd><code>signature(object = "onesidedBiasType")</code>:
-accessor function for slot <code>sign</code>. </dd>
-<dt>sign<-</dt><dd><code>signature(object = "onesidedBiasType", value = "numeric")</code>:
-replacement function for slot <code>sign</code>. </dd>
-</dl>
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"BiasType"</code>, directly.<br>
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="BiasType-class.html">BiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-positiveBias()
-## The function is currently defined as
-function(){ new("onesidedBiasType", name = "positive Bias", sign = 1) }
-
-negativeBias()
-## The function is currently defined as
-function(){ new("onesidedBiasType", name = "negative Bias", sign = -1) }
-
-pB <- positiveBias()
-sign(pB)
-try(sign(pB) <- -2) ## error
-sign(pB) <- -1
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/optIC.html
===================================================================
--- pkg/ROptEst/chm/optIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/optIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -34,12 +34,14 @@
optIC(model, risk)
## S4 method for signature 'InfRobModel, asRisk':
-optIC(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
+optIC(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
## S4 method for signature 'InfRobModel, asUnOvShoot':
-optIC(model, risk, upper = 1e4, maxiter = 50,
- tol = .Machine$double.eps^0.4, warn = TRUE)
+optIC(model, risk, biastype = symmetricBias(),
+ upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE)
## S4 method for signature 'FixRobModel, fiUnOvShoot':
optIC(model, risk, sampleSize, upper = 1e4, maxiter = 50,
@@ -59,6 +61,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
<tr valign="top"><td><code>z.start</code></td>
<td>
initial value for the centering constant. </td></tr>
@@ -154,7 +159,7 @@
<h3>See Also</h3>
<p>
-<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>, <code><a href="RiskType-class.html">RiskType-class</a></code>
+<code><a onclick="findlink('RobAStBase', 'InfluenceCurve-class.html')" style="text-decoration: underline; color: blue; cursor: hand">InfluenceCurve-class</a></code>, <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>
</p>
@@ -169,8 +174,17 @@
checkIC(IC0, B)
</pre>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Modified: pkg/ROptEst/chm/optRisk.html
===================================================================
--- pkg/ROptEst/chm/optRisk.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/optRisk.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -30,9 +30,13 @@
<pre>
optRisk(model, risk, ...)
+## S4 method for signature 'L2ParamFamily, asCov':
+optRisk(model, risk)
+
## S4 method for signature 'InfRobModel, asRisk':
-optRisk(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
- maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+optRisk(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
## S4 method for signature 'FixRobModel, fiUnOvShoot':
optRisk(model, risk, sampleSize, upper = 1e4, maxiter = 50,
@@ -52,6 +56,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>BiasType</code> </td></tr>
<tr valign="top"><td><code>z.start</code></td>
<td>
initial value for the centering constant. </td></tr>
@@ -138,7 +145,7 @@
<h3>See Also</h3>
<p>
-<code><a href="RiskType-class.html">RiskType-class</a></code>
+<code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>
</p>
@@ -148,8 +155,17 @@
optRisk(model = NormLocationScaleFamily(), risk = asCov())
</pre>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Deleted: pkg/ROptEst/chm/positiveBias.html
===================================================================
--- pkg/ROptEst/chm/positiveBias.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/positiveBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Generating function for onesidedBiasType-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>positiveBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: positiveBias">
-<param name="keyword" value=" Generating function for onesidedBiasType-class">
-</object>
-
-
-<h2>Generating function for onesidedBiasType-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"onesidedBias"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>positiveBias(name = "positive Bias")</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-name of the bias type</td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"onesidedBias"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="onesidedBiasType-class.html">onesidedBiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-positiveBias()
-
-## The function is currently defined as
-function(){ new("onesidedBiasType", name = "positive Bias", sign = 1) }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/radiusMinimaxIC.html
===================================================================
--- pkg/ROptEst/chm/radiusMinimaxIC.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/radiusMinimaxIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -29,7 +29,8 @@
## S4 method for signature 'L2ParamFamily,
## UncondNeighborhood, asGRisk':
-radiusMinimaxIC(L2Fam, neighbor, risk,
+radiusMinimaxIC(
+ L2Fam, neighbor, risk, biastype = symmetricBias(),
loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
</pre>
@@ -50,6 +51,9 @@
<tr valign="top"><td><code>...</code></td>
<td>
additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
<tr valign="top"><td><code>loRad</code></td>
<td>
the lower end point of the interval to be searched. </td></tr>
@@ -90,7 +94,8 @@
<h3>Author(s)</h3>
<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
</p>
@@ -126,6 +131,6 @@
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Deleted: pkg/ROptEst/chm/symmetricBias.html
===================================================================
--- pkg/ROptEst/chm/symmetricBias.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/symmetricBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,83 +0,0 @@
-<html><head><title>Generating function for symmetricBias-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>symmetricBias(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: symmetricBias">
-<param name="keyword" value=" Generating function for symmetricBias-class">
-</object>
-
-
-<h2>Generating function for symmetricBias-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"symmetricBias"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>symmetricBias(name = "symmetric Bias")</pre>
-
-
-<h3>Arguments</h3>
-
-<table summary="R argblock">
-<tr valign="top"><td><code>name</code></td>
-<td>
-name of the bias type</td></tr>
-</table>
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"symmetricBias"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="symmetricBiasType-class.html">symmetricBiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-symmetricBias()
-
-## The function is currently defined as
-function(){ new("symmetricBias", name = "symmetric Bias") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Deleted: pkg/ROptEst/chm/symmetricBiasType-class.html
===================================================================
--- pkg/ROptEst/chm/symmetricBiasType-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/symmetricBiasType-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,93 +0,0 @@
-<html><head><title>symmetric Bias Type</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>symmetricBiasType-class(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: symmetricBiasType-class">
-<param name="keyword" value=" symmetric Bias Type">
-</object>
-
-
-<h2>symmetric Bias Type</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Class of symmetric bias types.
-</p>
-
-
-<h3>Objects from the Class</h3>
-
-<p>
-Objects can be created by calls of the form <code>new("symmetricBiasType", ...)</code>.
-More frequently they are created via the generating function
-<code>symmetricBias</code>.
-</p>
-
-
-<h3>Slots</h3>
-
-<dl>
-<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>.</dd>
-</dl>
-
-<h3>Methods</h3>
-
-<p>
-No methods defined with class "symmetricBiasType" in the signature.
-</p>
-
-
-<h3>Extends</h3>
-
-<p>
-Class <code>"BiasType"</code>, directly.<br>
-</p>
-
-
-<h3>Author(s)</h3>
-
-<p>
-Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
-Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="BiasType-class.html">BiasType-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-symmetricBias()
-## The function is currently defined as
-function(){ new("symmetricBiasType", name = "symmetric Bias") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/trAsCov-class.html
===================================================================
--- pkg/ROptEst/chm/trAsCov-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/trAsCov-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -65,7 +65,7 @@
<h3>See Also</h3>
<p>
-<code><a href="asRisk-class.html">asRisk-class</a></code>, <code><a href="trAsCov.html">trAsCov</a></code>
+<code><a onclick="findlink('distrMod', 'asRisk-class.html')" style="text-decoration: underline; color: blue; cursor: hand">asRisk-class</a></code>, <code><a onclick="findlink('distrMod', 'trAsCov.html')" style="text-decoration: underline; color: blue; cursor: hand">trAsCov</a></code>
</p>
@@ -75,8 +75,17 @@
new("trAsCov")
</pre>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Deleted: pkg/ROptEst/chm/trAsCov.html
===================================================================
--- pkg/ROptEst/chm/trAsCov.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/trAsCov.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,71 +0,0 @@
-<html><head><title>Generating function for trAsCov-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>trAsCov(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: trAsCov">
-<param name="keyword" value=" Generating function for trAsCov-class">
-</object>
-
-
-<h2>Generating function for trAsCov-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"trAsCov"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>trAsCov()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"trAsCov"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
-</p>
-<p>
-Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
-Bayreuth: Dissertation.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="trAsCov-class.html">trAsCov-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-trAsCov()
-
-## The function is currently defined as
-function(){ new("trAsCov") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/chm/trFiCov-class.html
===================================================================
--- pkg/ROptEst/chm/trFiCov-class.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/trFiCov-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -62,7 +62,7 @@
<h3>See Also</h3>
<p>
-<code><a href="fiRisk-class.html">fiRisk-class</a></code>, <code><a href="trFiCov.html">trFiCov</a></code>
+<code><a onclick="findlink('distrMod', 'fiRisk-class.html')" style="text-decoration: underline; color: blue; cursor: hand">fiRisk-class</a></code>, <code><a onclick="findlink('distrMod', 'trFiCov.html')" style="text-decoration: underline; color: blue; cursor: hand">trFiCov</a></code>
</p>
@@ -72,8 +72,17 @@
new("trFiCov")
</pre>
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
</body></html>
Deleted: pkg/ROptEst/chm/trFiCov.html
===================================================================
--- pkg/ROptEst/chm/trFiCov.html 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/chm/trFiCov.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,68 +0,0 @@
-<html><head><title>Generating function for trFiCov-class</title>
-<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
-<link rel="stylesheet" type="text/css" href="Rchm.css">
-</head>
-<body>
-
-<table width="100%"><tr><td>trFiCov(ROptEst)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
-<param name="keyword" value="R: trFiCov">
-<param name="keyword" value=" Generating function for trFiCov-class">
-</object>
-
-
-<h2>Generating function for trFiCov-class</h2>
-
-
-<h3>Description</h3>
-
-<p>
-Generates an object of class <code>"trFiCov"</code>.
-</p>
-
-
-<h3>Usage</h3>
-
-<pre>trFiCov()</pre>
-
-
-<h3>Value</h3>
-
-<p>
-Object of class <code>"trFiCov"</code></p>
-
-<h3>Author(s)</h3>
-
-<p>
-Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
-</p>
-
-
-<h3>References</h3>
-
-<p>
-Ruckdeschel, P. and Kohl, M. (2005) How to approximate
-the finite sample risk of M-estimators.
-</p>
-
-
-<h3>See Also</h3>
-
-<p>
-<code><a href="trFiCov-class.html">trFiCov-class</a></code>
-</p>
-
-
-<h3>Examples</h3>
-
-<pre>
-trFiCov()
-
-## The function is currently defined as
-function(){ new("trFiCov") }
-</pre>
-
-
-
-<hr><div align="center">[Package <em>ROptEst</em> version 0.5.0 <a href="00Index.html">Index]</a></div>
-
-</body></html>
Modified: pkg/ROptEst/man/getAsRisk.Rd
===================================================================
--- pkg/ROptEst/man/getAsRisk.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getAsRisk.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,17 +1,18 @@
\name{getAsRisk}
\alias{getAsRisk}
\alias{getAsRisk-methods}
-\alias{getAsRisk,asMSE,UnivariateDistribution,Neighborhood-method}
-\alias{getAsRisk,asMSE,EuclRandVariable,Neighborhood-method}
-\alias{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood-method}
-\alias{getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood-method}
-\alias{getAsRisk,asBias,RealRandVariable,ContNeighborhood-method}
-\alias{getAsRisk,asCov,UnivariateDistribution,ContNeighborhood-method}
-\alias{getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood-method}
-\alias{getAsRisk,asCov,RealRandVariable,ContNeighborhood-method}
-\alias{getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood-method}
-\alias{getAsRisk,trAsCov,RealRandVariable,ContNeighborhood-method}
-\alias{getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood-method}
+\alias{getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method}
+\alias{getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method}
+\alias{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
+\alias{getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method}
+\alias{getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
+\alias{getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method}
+\alias{getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method}
+\alias{getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method}
+\alias{getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method}
+\alias{getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method}
\title{Generic Function for Computation of Asymptotic Risks}
\description{
@@ -20,36 +21,40 @@
other functions.
}
\usage{
-getAsRisk(risk, L2deriv, neighbor, ...)
+getAsRisk(risk, L2deriv, neighbor, biastype, ...)
-\S4method{getAsRisk}{asMSE,UnivariateDistribution,Neighborhood}(risk, L2deriv, neighbor, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asMSE,UnivariateDistribution,Neighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
-\S4method{getAsRisk}{asMSE,EuclRandVariable,Neighborhood}(risk, L2deriv, neighbor, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asMSE,EuclRandVariable,Neighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
-\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood}(risk, L2deriv, neighbor, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, trafo)
-\S4method{getAsRisk}{asBias,UnivariateDistribution,TotalVarNeighborhood}(risk, L2deriv, neighbor, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, trafo)
-\S4method{getAsRisk}{asBias,RealRandVariable,ContNeighborhood}(risk, L2deriv, neighbor, Distr, L2derivDistrSymm, trafo,
+\S4method{getAsRisk}{asBias,RealRandVariable,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
z.start, A.start, maxiter, tol)
-\S4method{getAsRisk}{asCov,UnivariateDistribution,ContNeighborhood}(risk, L2deriv, neighbor, clip, cent, stand)
+\S4method{getAsRisk}{asCov,UnivariateDistribution,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
-\S4method{getAsRisk}{asCov,UnivariateDistribution,TotalVarNeighborhood}(risk, L2deriv, neighbor, clip, cent, stand)
+\S4method{getAsRisk}{asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
-\S4method{getAsRisk}{asCov,RealRandVariable,ContNeighborhood}(risk, L2deriv, neighbor, Distr, clip, cent, stand)
+\S4method{getAsRisk}{asCov,RealRandVariable,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
-\S4method{getAsRisk}{trAsCov,UnivariateDistribution,UncondNeighborhood}(risk, L2deriv, neighbor, clip, cent, stand)
+\S4method{getAsRisk}{trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
-\S4method{getAsRisk}{trAsCov,RealRandVariable,ContNeighborhood}(risk, L2deriv, neighbor, Distr, clip, cent, stand)
+\S4method{getAsRisk}{trAsCov,RealRandVariable,ContNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
-\S4method{getAsRisk}{asUnOvShoot,UnivariateDistribution,UncondNeighborhood}(risk, L2deriv, neighbor, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+\S4method{getAsRisk}{asSemivar,UnivariateDistribution,Neighborhood,onesidedBias}(risk, L2deriv, neighbor, biastype,
+ clip, cent, stand, trafo)
}
\arguments{
\item{risk}{ object of class \code{"asRisk"}. }
\item{L2deriv}{ L2-derivative of some L2-differentiable family
of probability distributions. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{biastype}{ object of class \code{"BiasType"}. }
\item{\dots}{ additional parameters. }
\item{clip}{ optimal clipping bound. }
\item{cent}{ optimal centering constant. }
@@ -66,43 +71,47 @@
\value{The asymptotic risk is computed.}
\section{Methods}{
\describe{
- \item{risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood":}{
+ \item{risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "BiasType":}{
computes asymptotic mean square error in methods for
function \code{getInfRobIC}. }
- \item{risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood":}{
+ \item{risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "BiasType":}{
computes asymptotic mean square error in methods for
function \code{getInfRobIC}. }
- \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood":}{
+ \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
- \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood":}{
+ \item{risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
- \item{risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood":}{
+ \item{risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":}{
computes standardized asymptotic bias in methods for function \code{getInfRobIC}. }
- \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood":}{
+ \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":}{
computes asymptotic covariance in methods for function \code{getInfRobIC}. }
- \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood":}{
+ \item{risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":}{
computes asymptotic covariance in methods for function \code{getInfRobIC}. }
- \item{risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood":}{
+ \item{risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":}{
computes asymptotic covariance in methods for function \code{getInfRobIC}. }
- \item{risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood":}{
+ \item{risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":}{
computes trace of asymptotic covariance in methods
for function \code{getInfRobIC}. }
- \item{risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood":}{
+ \item{risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":}{
computes trace of asymptotic covariance in methods for
function \code{getInfRobIC}. }
- \item{risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood":}{
+ \item{risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":}{
computes asymptotic under-/overshoot risk in methods for
function \code{getInfRobIC}. }
+
+ \item{risk = "asSemivar", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "onesidedBias":}{
+ computes asymptotic semivariance in methods for
+ function \code{getInfRobIC}. }
}}
\references{
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
@@ -115,7 +124,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{asRisk-class}}}
+\seealso{\code{\link[distrMod]{asRisk-class}}}
%\examples{}
\concept{asymptotic risk}
\concept{risk}
Added: pkg/ROptEst/man/getBiasIC.Rd
===================================================================
--- pkg/ROptEst/man/getBiasIC.Rd (rev 0)
+++ pkg/ROptEst/man/getBiasIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,76 @@
+\name{getBiasIC}
+\alias{getBiasIC}
+\alias{getBiasIC-methods}
+\alias{getBiasIC,IC,ContNeighborhood,missing,BiasType-method}
+\alias{getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method}
+\alias{getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method}
+\alias{getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method}
+
+\title{Generic function for the computation of the asymptotic bias for an IC}
+\description{
+ Generic function for the computation of the asymptotic bias for an IC.
+}
+\usage{
+getBiasIC(IC, neighbor, L2Fam, biastype, ...)
+
+
+\S4method{getBiasIC}{IC,ContNeighborhood,missing,BiasType}(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+\S4method{getBiasIC}{IC,ContNeighborhood,L2ParamFamily,BiasType}(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+\S4method{getBiasIC}{IC,TotalVarNeighborhood,missing,BiasType}(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+\S4method{getBiasIC}{IC,TotalVarNeighborhood,L2ParamFamily,BiasType}(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+}
+\arguments{
+ \item{IC}{ object of class \code{"InfluenceCurve"} }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
+ \item{biastype}{ object of class \code{"BiasType"}. }
+ \item{\dots}{ additional parameters }
+ \item{tol}{ the desired accuracy (convergence tolerance).}
+}
+\details{To make sure that the results are valid, it is recommended
+ to include an additional check of the IC properties of \code{IC}
+ using \code{checkIC}.}
+\value{The asymptotic bias of an IC is computed.}
+\section{Methods}{
+\describe{
+
+ \item{IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+ biastype = "BiasType"}{ asymptotic bias of \code{IC} in case of convex contamination neighborhoods
+ and symmetric bias. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+ biastype = "BiasType"}{ asymptotic bias of \code{IC} under \code{L2Fam}
+ in case of convex contamination neighborhoods and symmetric bias. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+ biastype = "BiasType"}{ asymptotic bias of \code{IC} in case of total variation neighborhoods
+ and symmetric bias. }
+
+ \item{IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+ biastype = "BiasType"}{ asymptotic bias of \code{IC} under \code{L2Fam}
+ in case of total variation neighborhoods and symmetric bias. }
+}}
+\references{
+ Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+
+\note{This generic function is still under construction.}
+\seealso{\code{\link{getRiskIC-methods}}, \code{\link[RobAStBase]{InfRobModel-class}}}
+%\examples{}
+\concept{influence curve}
+\keyword{}
Modified: pkg/ROptEst/man/getFiRisk.Rd
===================================================================
--- pkg/ROptEst/man/getFiRisk.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getFiRisk.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -13,11 +13,11 @@
\usage{
getFiRisk(risk, Distr, neighbor, ...)
-\S4method{getFiRisk}{fiUnOvShoot,Norm,ContNeighborhood}(risk, Distr, neighbor,
- clip, stand, sampleSize, Algo, cont)
+\S4method{getFiRisk}{fiUnOvShoot,Norm,ContNeighborhood}(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
-\S4method{getFiRisk}{fiUnOvShoot,Norm,TotalVarNeighborhood}(risk, Distr, neighbor,
- clip, stand, sampleSize, Algo, cont)
+\S4method{getFiRisk}{fiUnOvShoot,Norm,TotalVarNeighborhood}(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
}
\arguments{
\item{risk}{ object of class \code{"RiskType"}. }
@@ -56,7 +56,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{fiRisk-class}}}
+\seealso{\code{\link[distrMod]{fiRisk-class}}}
%\examples{}
\concept{finite-sample risk}
\concept{risk}
Modified: pkg/ROptEst/man/getFixClip.Rd
===================================================================
--- pkg/ROptEst/man/getFixClip.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getFixClip.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -11,7 +11,7 @@
rarely called directly. It is used to compute optimally robust ICs.
}
\usage{
-getFixClip(clip, Distr, risk, neighbor, ...)
+getFixClip(clip, Distr, risk, neighbor, ...)
\S4method{getFixClip}{numeric,Norm,fiUnOvShoot,ContNeighborhood}(clip, Distr, risk, neighbor)
@@ -43,7 +43,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{ContIC-class}}, \code{\link{TotalVarIC-class}}}
+\seealso{\code{\link[RobAStBase]{ContIC-class}}, \code{\link[RobAStBase]{TotalVarIC-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/getFixRobIC.Rd
===================================================================
--- pkg/ROptEst/man/getFixRobIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getFixRobIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -13,7 +13,7 @@
getFixRobIC(Distr, risk, neighbor, ...)
\S4method{getFixRobIC}{Norm,fiUnOvShoot,UncondNeighborhood}(Distr, risk, neighbor,
- sampleSize, upper, maxiter, tol, warn, Algo, cont)
+ sampleSize, upper, maxiter, tol, warn, Algo, cont)
}
\arguments{
\item{Distr}{ object of class \code{"Distribution"}. }
@@ -45,7 +45,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{FixRobModel-class}}}
+\seealso{\code{\link[RobAStBase]{FixRobModel-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/getIneffDiff.Rd
===================================================================
--- pkg/ROptEst/man/getIneffDiff.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getIneffDiff.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,7 +1,7 @@
\name{getIneffDiff}
\alias{getIneffDiff}
\alias{getIneffDiff-methods}
-\alias{getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE-method}
+\alias{getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method}
\title{Generic Function for the Computation of Inefficiency Differences}
\description{
@@ -10,9 +10,10 @@
the radius minimax IC and the least favorable radius.
}
\usage{
-getIneffDiff(radius, L2Fam, neighbor, risk, ...)
+getIneffDiff(radius, L2Fam, neighbor, risk, biastype, ...)
-\S4method{getIneffDiff}{numeric,L2ParamFamily,UncondNeighborhood,asMSE}(radius, L2Fam, neighbor, risk, loRad, upRad,
+\S4method{getIneffDiff}{numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType}(
+ radius, L2Fam, neighbor, risk, biastype = symmetricBias(), loRad, upRad,
loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
}
\arguments{
@@ -20,6 +21,7 @@
\item{L2Fam}{ L2-differentiable family of probability measures. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
\item{risk}{ object of class \code{"RiskType"}. }
+ \item{biastype}{ object of class \code{"BiasType"}. }
\item{\dots}{ additional parameters }
\item{loRad}{ the lower end point of the interval to be searched. }
\item{upRad}{ the upper end point of the interval to be searched. }
@@ -39,7 +41,7 @@
\section{Methods}{
\describe{
\item{radius = "numeric", L2Fam = "L2ParamFamily",
- neighbor = "UncondNeighborhood", risk = "asMSE":}{
+ neighbor = "UncondNeighborhood", risk = "asMSE", biastype = "BiasType":}{
computes difference of asymptotic MSE--inefficiency for
the boundaries of a given radius interval.}
}}
@@ -50,10 +52,14 @@
Humboldt University, Berlin; also available under
\url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
\seealso{\code{\link{radiusMinimaxIC}}, \code{\link{leastFavorableRadius}}}
%\examples{}
Modified: pkg/ROptEst/man/getInfCent.Rd
===================================================================
--- pkg/ROptEst/man/getInfCent.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getInfCent.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,9 +1,11 @@
\name{getInfCent}
\alias{getInfCent}
\alias{getInfCent-methods}
-\alias{getInfCent,UnivariateDistribution,ContNeighborhood-method}
-\alias{getInfCent,UnivariateDistribution,TotalVarNeighborhood-method}
-\alias{getInfCent,RealRandVariable,ContNeighborhood-method}
+\alias{getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
+\alias{getInfCent,RealRandVariable,ContNeighborhood,BiasType-method}
+\alias{getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method}
+\alias{getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}
\title{Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound}
\description{
@@ -14,18 +16,28 @@
compute optimally robust ICs.
}
\usage{
-getInfCent(L2deriv, neighbor, ...)
+getInfCent(L2deriv, neighbor, biastype, ...)
-\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood}(L2deriv, neighbor, clip, cent, tol.z, symm, trafo)
+\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
-\S4method{getInfCent}{UnivariateDistribution,TotalVarNeighborhood}(L2deriv, neighbor, clip, cent, tol.z, symm, trafo)
+\S4method{getInfCent}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
-\S4method{getInfCent}{RealRandVariable,ContNeighborhood}(L2deriv, neighbor, z.comp, stand, cent, clip)
+\S4method{getInfCent}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+
+\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,onesidedBias}(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+
+\S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
of probability measures. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{\dots}{ additional parameters. }
\item{clip}{ optimal clipping bound. }
\item{cent}{ optimal centering constant. }
@@ -40,24 +52,34 @@
\value{The optimal centering constant is computed.}
\section{Methods}{
\describe{
- \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood"}{
- computation of optimal centering constant. }
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType"}{
+ computation of optimal centering constant for symmetric bias. }
- \item{L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood"}{
- computation of optimal lower clipping bound. }
+ \item{L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType"}{
+ computation of optimal lower clipping bound for symmetric bias. }
- \item{L2deriv = "RealRandVariable", neighbor = "ContNeighborhood"}{
- computation of optimal centering constant. }
+ \item{L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType"}{
+ computation of optimal centering constant for symmetric bias. }
+
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias"}{
+ computation of optimal centering constant for onesided bias. }
+
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias"}{
+ computation of optimal centering constant for asymmetric bias. }
}}
\references{
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
-\seealso{\code{\link{ContIC-class}}, \code{\link{TotalVarIC-class}}}
+\seealso{\code{\link[RobAStBase]{ContIC-class}}, \code{\link[RobAStBase]{TotalVarIC-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/getInfClip.Rd
===================================================================
--- pkg/ROptEst/man/getInfClip.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getInfClip.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -5,6 +5,7 @@
\alias{getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method}
\alias{getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood-method}
\alias{getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method}
+\alias{getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method}
\title{Generic Function for the Computation of the Optimal Clipping Bound}
\description{
@@ -15,13 +16,15 @@
\usage{
getInfClip(clip, L2deriv, risk, neighbor, ...)
-\S4method{getInfClip}{numeric,UnivariateDistribution,asMSE,ContNeighborhood}(clip, L2deriv, risk, neighbor, cent, symm, trafo)
+\S4method{getInfClip}{numeric,UnivariateDistribution,asMSE,ContNeighborhood}(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
-\S4method{getInfClip}{numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood}(clip, L2deriv, risk, neighbor, cent, symm, trafo)
+\S4method{getInfClip}{numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood}(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
-\S4method{getInfClip}{numeric,EuclRandVariable,asMSE,ContNeighborhood}(clip, L2deriv, risk, neighbor, Distr, stand, cent, trafo)
+\S4method{getInfClip}{numeric,EuclRandVariable,asMSE,ContNeighborhood}(clip, L2deriv, risk, neighbor, Distr, stand, biastype, cent, trafo)
-\S4method{getInfClip}{numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(clip, L2deriv, risk, neighbor, cent, symm, trafo)
+\S4method{getInfClip}{numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+\S4method{getInfClip}{numeric,UnivariateDistribution,asSemivar,ContNeighborhood}(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
}
\arguments{
\item{clip}{ positive real: clipping bound }
@@ -30,6 +33,7 @@
\item{risk}{ object of class \code{"RiskType"}. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
\item{\dots}{ additional parameters. }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{cent}{ optimal centering constant. }
\item{stand}{ standardizing matrix. }
\item{Distr}{ object of class \code{"Distribution"}. }
@@ -44,6 +48,7 @@
risk = "asMSE", neighbor = "ContNeighborhood"}{
optimal clipping bound for asymtotic mean square error. }
+
\item{clip = "numeric", L2deriv = "UnivariateDistribution",
risk = "asMSE", neighbor = "TotalVarNeighborhood"}{
optimal clipping bound for asymtotic mean square error. }
@@ -55,18 +60,26 @@
\item{clip = "numeric", L2deriv = "UnivariateDistribution",
risk = "asUnOvShoot", neighbor = "UncondNeighborhood"}{
optimal clipping bound for asymtotic under-/overshoot risk. }
+
+ \item{clip = "numeric", L2deriv = "UnivariateDistribution",
+ risk = "asSemivar", neighbor = "ContNeighborhood"}{
+ optimal clipping bound for asymtotic semivariance.}
}}
\references{
Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
-\seealso{\code{\link{ContIC-class}}, \code{\link{TotalVarIC-class}}}
+\seealso{\code{\link[RobAStBase]{ContIC-class}}, \code{\link[RobAStBase]{TotalVarIC-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/getInfGamma.Rd
===================================================================
--- pkg/ROptEst/man/getInfGamma.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getInfGamma.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,10 +1,12 @@
\name{getInfGamma}
\alias{getInfGamma}
\alias{getInfGamma-methods}
-\alias{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood-method}
-\alias{getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood-method}
-\alias{getInfGamma,RealRandVariable,asMSE,ContNeighborhood-method}
-\alias{getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood-method}
+\alias{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method}
+\alias{getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method}
+\alias{getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method}
+\alias{getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method}
+\alias{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method}
+\alias{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method}
\title{Generic Function for the Computation of the Optimal Clipping Bound}
\description{
@@ -13,21 +15,32 @@
to compute optimally robust ICs.
}
\usage{
-getInfGamma(L2deriv, risk, neighbor, ...)
+getInfGamma(L2deriv, risk, neighbor, biastype, ...)
-\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood}(L2deriv, risk, neighbor, cent, clip)
+\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood,BiasType}(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
-\S4method{getInfGamma}{UnivariateDistribution,asGRisk,TotalVarNeighborhood}(L2deriv, risk, neighbor, cent, clip)
+\S4method{getInfGamma}{UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType}(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
-\S4method{getInfGamma}{RealRandVariable,asMSE,ContNeighborhood}(L2deriv, risk, neighbor, Distr, stand, cent, clip)
+\S4method{getInfGamma}{RealRandVariable,asMSE,ContNeighborhood,BiasType}(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
-\S4method{getInfGamma}{UnivariateDistribution,asUnOvShoot,ContNeighborhood}(L2deriv, risk, neighbor, cent, clip)
+\S4method{getInfGamma}{UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType}(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias}(L2deriv,
+ risk, neighbor, biastype = positiveBias(), cent, clip)
+
+\S4method{getInfGamma}{UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias}(L2deriv,
+ risk, neighbor, biastype = asymmetricBias(), cent, clip)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
of probability measures. }
\item{risk}{ object of class \code{"RiskType"}. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{\dots}{ additional parameters }
\item{cent}{ optimal centering constant. }
\item{clip}{ optimal clipping bound. }
@@ -42,16 +55,28 @@
\section{Methods}{
\describe{
\item{L2deriv = "UnivariateDistribution", risk = "asMSE",
- neighbor = "ContNeighborhood"}{ used by \code{getInfClip}. }
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{ used by \code{getInfClip} for symmetric bias. }
\item{L2deriv = "UnivariateDistribution", risk = "asGRisk",
- neighbor = "TotalVarNeighborhood"}{ used by \code{getInfClip}. }
+ neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"}{ used by \code{getInfClip} for symmetric bias. }
\item{L2deriv = "RealRandVariable", risk = "asMSE",
- neighbor = "ContNeighborhood"}{ used by \code{getInfClip}. }
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{ used by \code{getInfClip} for symmetric bias. }
\item{L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",
- neighbor = "ContNeighborhood"}{ used by \code{getInfClip}. }
+ neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{ used by \code{getInfClip} for symmetric bias. }
+
+ \item{L2deriv = "UnivariateDistribution", risk = "asMSE",
+ neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"}{ used by \code{getInfClip} for onesided bias. }
+
+ \item{L2deriv = "UnivariateDistribution", risk = "asMSE",
+ neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"}{ used by \code{getInfClip} for asymmetric bias. }
}}
\references{
Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
@@ -59,16 +84,20 @@
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
- General Loss Functions. Statistics & Decisions (submitted).
+ General Loss Functions. Statistics & Decisions \emph{22}, 201-223.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
-\seealso{\code{\link{asGRisk-class}}, \code{\link{asMSE-class}},
- \code{\link{asUnOvShoot-class}}, \code{\link{ContIC-class}},
- \code{\link{TotalVarIC-class}}}
+\seealso{\code{\link[distrMod]{asGRisk-class}}, \code{\link[distrMod]{asMSE-class}},
+ \code{\link[distrMod]{asUnOvShoot-class}}, \code{\link[RobAStBase]{ContIC-class}},
+ \code{\link[RobAStBase]{TotalVarIC-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/getInfRobIC.Rd
===================================================================
--- pkg/ROptEst/man/getInfRobIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getInfRobIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -4,8 +4,7 @@
\alias{getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method}
\alias{getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method}
\alias{getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method}
-\alias{getInfRobIC,UnivariateDistribution,asBias,ContNeighborhood-method}
-\alias{getInfRobIC,UnivariateDistribution,asBias,TotalVarNeighborhood-method}
+\alias{getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method}
\alias{getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method}
\alias{getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method}
\alias{getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method}
@@ -28,28 +27,25 @@
\S4method{getInfRobIC}{RealRandVariable,asCov,ContNeighborhood}(L2deriv, risk, neighbor, Distr, Finfo, trafo)
-\S4method{getInfRobIC}{UnivariateDistribution,asBias,ContNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
+\S4method{getInfRobIC}{UnivariateDistribution,asBias,UncondNeighborhood}(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
-\S4method{getInfRobIC}{UnivariateDistribution,asBias,TotalVarNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
- upper, maxiter, tol, warn)
-
\S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
-\S4method{getInfRobIC}{UnivariateDistribution,asHampel,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
+\S4method{getInfRobIC}{UnivariateDistribution,asHampel,UncondNeighborhood}(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
-\S4method{getInfRobIC}{RealRandVariable,asHampel,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+\S4method{getInfRobIC}{RealRandVariable,asHampel,ContNeighborhood}(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
-\S4method{getInfRobIC}{UnivariateDistribution,asGRisk,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
+\S4method{getInfRobIC}{UnivariateDistribution,asGRisk,UncondNeighborhood}(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
-\S4method{getInfRobIC}{RealRandVariable,asGRisk,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+\S4method{getInfRobIC}{RealRandVariable,asGRisk,ContNeighborhood}(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
-\S4method{getInfRobIC}{UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo,
+\S4method{getInfRobIC}{UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
upper, maxiter, tol, warn)
}
\arguments{
@@ -58,6 +54,7 @@
\item{risk}{ object of class \code{"RiskType"}. }
\item{neighbor}{ object of class \code{"Neighborhood"}. }
\item{\dots}{ additional parameters. }
+ \item{biastype}{ object of class \code{"BiasType"}. }
\item{Distr}{ object of class \code{"Distribution"}. }
\item{symm}{ logical: indicating symmetry of \code{L2deriv}. }
\item{DistrSymm}{ object of class \code{"DistributionSymmetry"}. }
@@ -93,15 +90,10 @@
(\eqn{k > 1}) where the underlying distribution is univariate. }
\item{L2deriv = "UnivariateDistribution", risk = "asBias",
- neighbor = "ContNeighborhood"}{
+ neighbor = "UncondNeighborhood"}{
computes the bias optimal influence curve for L2 differentiable
parametric families with unknown one-dimensional parameter. }
- \item{L2deriv = "UnivariateDistribution", risk = "asBias",
- neighbor = "TotalVarNeighborhood"}{
- computes the bias optimal influence curve for L2 differentiable
- parametric families with unknown one-dimensional parameter. }
-
\item{L2deriv = "RealRandVariable", risk = "asBias",
neighbor = "ContNeighborhood"}{
computes the bias optimal influence curve for L2 differentiable
@@ -137,16 +129,22 @@
asymptotic under-/overshoot risk. }
}}
\references{
- Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106-115.
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+ Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+ General Loss Functions. Statistics & Decisions \bold{22}: 201-223.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{InfRobModel-class}}}
+\seealso{\code{\link[RobAStBase]{InfRobModel-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Modified: pkg/ROptEst/man/getInfStand.Rd
===================================================================
--- pkg/ROptEst/man/getInfStand.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getInfStand.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,9 +1,11 @@
\name{getInfStand}
\alias{getInfStand}
\alias{getInfStand-methods}
-\alias{getInfStand,UnivariateDistribution,ContNeighborhood-method}
-\alias{getInfStand,UnivariateDistribution,TotalVarNeighborhood-method}
-\alias{getInfStand,RealRandVariable,ContNeighborhood-method}
+\alias{getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
+\alias{getInfStand,RealRandVariable,ContNeighborhood,BiasType-method}
+\alias{getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method}
+\alias{getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}
\title{ Generic Function for the Computation of the Standardizing Matrix }
\description{
@@ -12,18 +14,28 @@
is rarely called directly. It is used to compute optimally robust ICs.
}
\usage{
-getInfStand(L2deriv, neighbor, ...)
+getInfStand(L2deriv, neighbor, biastype, ...)
-\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood}(L2deriv, neighbor, clip, cent, trafo)
+\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
-\S4method{getInfStand}{UnivariateDistribution,TotalVarNeighborhood}(L2deriv, neighbor, clip, cent, trafo)
+\S4method{getInfStand}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
-\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood}(L2deriv, neighbor, Distr, A.comp, stand, clip, cent, trafo)
+\S4method{getInfStand}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+
+\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, trafo)
+
+\S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, trafo)
}
\arguments{
\item{L2deriv}{ L2-derivative of some L2-differentiable family
of probability measures. }
\item{neighbor}{ object of class \code{"Neighborhood"} }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{\dots}{ additional parameters }
\item{clip}{ optimal clipping bound. }
\item{cent}{ optimal centering constant. }
@@ -37,24 +49,39 @@
\value{The standardizing matrix is computed.}
\section{Methods}{
\describe{
- \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood"}{
- computes standardizing matrix. }
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{
+ computes standardizing matrix for symmetric bias. }
- \item{L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood"}{
- computes standardizing matrix. }
+ \item{L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"}{
+ computes standardizing matrix for symmetric bias. }
- \item{L2deriv = "RealRandVariable", neighbor = "ContNeighborhood"}{
- computes standardizing matrix. }
+ \item{L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{
+ computes standardizing matrix for symmetric bias. }
+
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+ biastype = "onesidedBias"}{
+ computes standardizing matrix for onesided bias. }
+
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"}{
+ computes standardizing matrix for asymmetric bias. }
}}
\references{
Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
-\seealso{\code{\link{ContIC-class}}, \code{\link{TotalVarIC-class}}}
+\seealso{\code{\link[RobAStBase]{ContIC-class}}, \code{\link[RobAStBase]{TotalVarIC-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Added: pkg/ROptEst/man/getL1normL2deriv.Rd
===================================================================
--- pkg/ROptEst/man/getL1normL2deriv.Rd (rev 0)
+++ pkg/ROptEst/man/getL1normL2deriv.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,36 @@
+\name{getL1normL2deriv}
+\alias{getL1normL2deriv}
+\alias{getL1normL2deriv-methods}
+\alias{getL1normL2deriv,UnivariateDistribution-method}
+\alias{getL1normL2deriv,RealRandVariable-method}
+
+\title{Calculation of L1 norm of L2derivative}
+\description{
+ Methods to calculate the L1 norm of the L2derivative in a smooth parametric model.
+}
+\usage{getL1normL2deriv(L2deriv, ...)
+\S4method{getL1normL2deriv}{UnivariateDistribution}(L2deriv,
+ cent, ...)
+
+\S4method{getL1normL2deriv}{UnivariateDistribution}(L2deriv,
+ cent, stand, Distr, ...)
+
+}
+%\details{}
+\arguments{
+ \item{L2deriv}{L2derivative of the model}
+ \item{cent}{centering Lagrange Multiplier}
+ \item{stand}{standardizing Lagrange Multiplier}
+ \item{Distr}{distribution of the L2derivative}
+ \item{...}{further arguments (not used at the moment)}
+}
+
+\value{L1 norm of the L2derivative}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+%\note{}
+\examples{
+##
+}
+\concept{L1norm}
+\keyword{}
+
Added: pkg/ROptEst/man/getL2normL2deriv.Rd
===================================================================
--- pkg/ROptEst/man/getL2normL2deriv.Rd (rev 0)
+++ pkg/ROptEst/man/getL2normL2deriv.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,23 @@
+\name{getL2normL2deriv}
+\alias{getL2normL2deriv}
+
+\title{Calculation of L2 norm of L2derivative}
+\description{
+ Function to calculate the L2 norm of the L2derivative in a smooth parametric model.
+}
+\usage{getL2normL2deriv(aFinfo, cent, ...)}
+%\details{}
+\arguments{
+ \item{aFinfo}{trace of the Fisher information}
+ \item{cent}{centering}
+ \item{...}{further arguments (not used at the moment)}
+}
+
+\value{L2 norm of the L2derivative}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+%\note{}
+\examples{
+##
+}
+\concept{L2norm}
+\keyword{}
Modified: pkg/ROptEst/man/getRiskIC.Rd
===================================================================
--- pkg/ROptEst/man/getRiskIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/getRiskIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -5,10 +5,8 @@
\alias{getRiskIC,IC,asCov,missing,L2ParamFamily-method}
\alias{getRiskIC,IC,trAsCov,missing,missing-method}
\alias{getRiskIC,IC,trAsCov,missing,L2ParamFamily-method}
-\alias{getRiskIC,IC,asBias,ContNeighborhood,missing-method}
-\alias{getRiskIC,IC,asBias,ContNeighborhood,L2ParamFamily-method}
-\alias{getRiskIC,IC,asBias,TotalVarNeighborhood,missing-method}
-\alias{getRiskIC,IC,asBias,TotalVarNeighborhood,L2ParamFamily-method}
+\alias{getRiskIC,IC,asBias,UncondNeighborhood,missing-method}
+\alias{getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method}
\alias{getRiskIC,IC,asMSE,UncondNeighborhood,missing-method}
\alias{getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method}
\alias{getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method}
@@ -30,18 +28,14 @@
\S4method{getRiskIC}{IC,trAsCov,missing,L2ParamFamily}(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
-\S4method{getRiskIC}{IC,asBias,ContNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+\S4method{getRiskIC}{IC,asBias,UncondNeighborhood,missing}(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
-\S4method{getRiskIC}{IC,asBias,ContNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+\S4method{getRiskIC}{IC,asBias,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
-\S4method{getRiskIC}{IC,asBias,TotalVarNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
+\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,missing}(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
-\S4method{getRiskIC}{IC,asBias,TotalVarNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
+\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
-\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,missing}(IC, risk, neighbor, tol = .Machine$double.eps^0.25)
-
-\S4method{getRiskIC}{IC,asMSE,UncondNeighborhood,L2ParamFamily}(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)
-
\S4method{getRiskIC}{TotalVarIC,asUnOvShoot,UncondNeighborhood,missing}(IC, risk, neighbor)
\S4method{getRiskIC}{IC,fiUnOvShoot,ContNeighborhood,missing}(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
@@ -54,6 +48,7 @@
\item{neighbor}{ object of class \code{"Neighborhood"}. }
\item{L2Fam}{ object of class \code{"L2ParamFamily"}. }
\item{\dots}{ additional parameters }
+ \item{biastype}{ object of class \code{"BiasType"}. }
\item{tol}{ the desired accuracy (convergence tolerance).}
\item{sampleSize}{ integer: sample size. }
\item{Algo}{ "A" or "B". }
@@ -121,7 +116,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
\note{This generic function is still under construction.}
-\seealso{\code{\link{getRiskIC-methods}}, \code{\link{InfRobModel-class}}}
+\seealso{\code{\link{getRiskIC-methods}}, \code{\link[RobAStBase]{InfRobModel-class}}}
%\examples{}
\concept{influence curve}
\keyword{}
Deleted: pkg/ROptEst/man/infoPlot.Rd
===================================================================
--- pkg/ROptEst/man/infoPlot.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/infoPlot.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,36 +0,0 @@
-\name{infoPlot}
-\alias{infoPlot}
-
-\title{Plot absolute and relative information}
-\description{
- Plot absolute and relative information of influence curves.
-}
-\usage{
-infoPlot(object)
-}
-\arguments{
- \item{object}{ object of class \code{"InfluenceCurve"} }
-}
-\details{
- Absolute information is defined as the square of the length
- of an IC. The relative information is defined as the
- absolute information of one component with respect to the
- absolute information of the whole IC; confer Section 8.1
- of Kohl (2005).
-}
-%\value{}
-\references{
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{L2ParamFamily-class}}, \code{\link{IC-class}}}
-\examples{
-N <- NormLocationScaleFamily(mean=0, sd=1)
-IC1 <- optIC(model = N, risk = asCov())
-infoPlot(IC1)
-}
-\concept{absolute information}
-\concept{relative information}
-\keyword{}
Deleted: pkg/ROptEst/man/ksEstimator.Rd
===================================================================
--- pkg/ROptEst/man/ksEstimator.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/ksEstimator.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,86 +0,0 @@
-\name{ksEstimator}
-\alias{ksEstimator}
-\alias{ksEstimator-methods}
-\alias{ksEstimator,numeric,Binom-method}
-\alias{ksEstimator,numeric,Pois-method}
-\alias{ksEstimator,numeric,Norm-method}
-\alias{ksEstimator,numeric,Lnorm-method}
-\alias{ksEstimator,numeric,Gumbel-method}
-\alias{ksEstimator,numeric,Exp-method}
-\alias{ksEstimator,numeric,Gammad-method}
-
-\title{Generic Function for the Computation of the Kolmogorov Minimum Distance Estimator}
-\description{
- Generic function for the computation of the Kolmogorov(-Smirnov)
- minimum distance estimator.
-}
-\usage{
-ksEstimator(x, distribution, ...)
-
-\S4method{ksEstimator}{numeric,Binom}(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-\S4method{ksEstimator}{numeric,Pois}(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-\S4method{ksEstimator}{numeric,Norm}(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-\S4method{ksEstimator}{numeric,Lnorm}(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-\S4method{ksEstimator}{numeric,Gumbel}(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-\S4method{ksEstimator}{numeric,Exp}(x, distribution, param, eps = .Machine$double.eps^0.5)
-
-\S4method{ksEstimator}{numeric,Gammad}(x, distribution, param, eps = .Machine$double.eps^0.5)
-}
-\arguments{
- \item{x}{ sample }
- \item{distribution}{ object of class \code{"Distribution"} }
- \item{\dots}{ additional parameters }
- \item{param}{ name of the unknown parameter. If missing all parameters
- of the corresponding distribution are estimated. }
- \item{eps}{ the desired accuracy (convergence tolerance). }
-}
-\details{In case of discrete distributions the Kolmogorov distance is computed and
- the parameters which lead to the minimum distance are returned. In case of
- absolutely continuous distributions \code{ks.test} is called and the parameters
- which minimize the corresponding test statistic are returned. }
-\value{The Kolmogorov minimum distance estimator is computed. Returns a list
- with components named like the parameters of \code{distribution}. }
-\section{Methods}{
-\describe{
- \item{x = "numeric", distribution = "Binom"}{ Binomial distributions. }
-
- \item{x = "numeric", distribution = "Pois"}{ Poisson distributions. }
-
- \item{x = "numeric", distribution = "Norm"}{ Normal distributions. }
-
- \item{x = "numeric", distribution = "Lnorm"}{ Lognormal distributions. }
-
- \item{x = "numeric", distribution = "Gumbel"}{ Gumbel distributions. }
-
- \item{x = "numeric", distribution = "Exp"}{ Exponential distributions. }
-
- \item{x = "numeric", distribution = "Gamma"}{ Gamma distributions. }
-}}
-\references{
- Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link[distr]{Distribution-class}}}
-\examples{
-x <- rnorm(100, mean = 1, sd = 2)
-ksEstimator(x=x, distribution = Norm()) # estimate mean and sd
-ksEstimator(x=x, distribution = Norm(mean = 1), param = "sd") # estimate sd
-ksEstimator(x=x, distribution = Norm(sd = 2), param = "mean") # estimate mean
-mean(x)
-median(x)
-sd(x)
-mad(x)
-}
-\concept{Kolmogorov minimum distance estimator}
-\concept{minimum distance estimator}
-\concept{estimator}
-\keyword{}
Modified: pkg/ROptEst/man/leastFavorableRadius.Rd
===================================================================
--- pkg/ROptEst/man/leastFavorableRadius.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/leastFavorableRadius.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -10,7 +10,8 @@
\usage{
leastFavorableRadius(L2Fam, neighbor, risk, ...)
-\S4method{leastFavorableRadius}{L2ParamFamily,UncondNeighborhood,asGRisk}(L2Fam, neighbor, risk, rho, upRad = 1,
+\S4method{leastFavorableRadius}{L2ParamFamily,UncondNeighborhood,asGRisk}(
+ L2Fam, neighbor, risk, biastype = symmetricBias(), rho, upRad = 1,
z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
tol = .Machine$double.eps^0.4, warn = FALSE)
}
@@ -19,6 +20,7 @@
\item{neighbor}{ object of class \code{"Neighborhood"}. }
\item{risk}{ object of class \code{"RiskType"}. }
\item{\dots}{ additional parameters }
+ \item{biastype}{ object of class \code{"BiasType"}. }
\item{upRad}{ the upper end point of the radius interval to be searched. }
\item{rho}{ The considered radius interval is: \eqn{[r \rho, r/\rho]}{[r*rho, r/rho]}
with \eqn{\rho\in(0,1)}{0 < rho < 1}. }
@@ -40,16 +42,23 @@
risk = "asGRisk"}{ computation of the least favorable radius. }
}}
\references{
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+ the Radius. Statistical Methods and Applications \emph{17}(1) 13-40.
+
Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
the Radius. Submitted. Appeared as discussion paper Nr. 81.
SFB 373 (Quantification and Simulation of Economic Processes),
Humboldt University, Berlin; also available under
\url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
\seealso{\code{\link{radiusMinimaxIC}}}
\examples{
Modified: pkg/ROptEst/man/locMEstimator.Rd
===================================================================
--- pkg/ROptEst/man/locMEstimator.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/locMEstimator.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -37,7 +37,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{InfluenceCurve-class}}}
+\seealso{\code{\link[RobAStBase]{InfluenceCurve-class}}}
%\examples{}
\concept{M estimator}
\concept{estimator}
Modified: pkg/ROptEst/man/lowerCaseRadius.Rd
===================================================================
--- pkg/ROptEst/man/lowerCaseRadius.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/lowerCaseRadius.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,40 +1,49 @@
\name{lowerCaseRadius}
\alias{lowerCaseRadius}
\alias{lowerCaseRadius-methods}
-\alias{lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE-method}
-\alias{lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE-method}
+\alias{lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method}
+\alias{lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method}
\title{Computation of the lower case radius}
\description{
The lower case radius is computed; confer Subsection 2.1.2
- in Kohl (2005).
+ in Kohl (2005) and formula (4.5) in Ruckdeschel (2005).
}
\usage{
-lowerCaseRadius(L2Fam, neighbor, risk, ...)
+lowerCaseRadius(L2Fam, neighbor, risk, biastype, ...)
}
\arguments{
\item{L2Fam}{ L2 differentiable parametric family }
\item{neighbor}{ object of class \code{"Neighborhood"} }
\item{risk}{ object of class \code{"RiskType"} }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{\dots}{ additional parameters }
}
%\details{}
\value{lower case radius}
\section{Methods}{
\describe{
- \item{L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE"}{
- lower case radius for risk \code{"asMSE"} in case of \code{"ContNeighborhood"}.}
+ \item{L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE",
+ biastype = "BiasType"}{
+ lower case radius for risk \code{"asMSE"} in case of \code{"ContNeighborhood"}
+ for symmetric bias.}
- \item{L2Fam = "L2ParamFamily", neighbor = "TotalVarNeighborhood", risk = "asMSE"}{
- lower case radius for risk \code{"asMSE"} in case of \code{"TotalVarNeighborhood"}.}
+ \item{L2Fam = "L2ParamFamily", neighbor = "TotalVarNeighborhood", risk = "asMSE",
+ biastype = "BiasType"}{
+ lower case radius for risk \code{"asMSE"} in case of \code{"TotalVarNeighborhood"};
+ (argument biastype is just for signature reasons).}
}}
\references{
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
-\seealso{\code{\link{L2ParamFamily-class}}, \code{\link{Neighborhood-class}}}
+\seealso{\code{\link[distrMod]{L2ParamFamily-class}}, \code{\link[RobAStBase]{Neighborhood-class}}}
\examples{
lowerCaseRadius(BinomFamily(size = 10), ContNeighborhood(), asMSE())
lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
Added: pkg/ROptEst/man/minmaxBias.Rd
===================================================================
--- pkg/ROptEst/man/minmaxBias.Rd (rev 0)
+++ pkg/ROptEst/man/minmaxBias.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,94 @@
+\name{minmaxBias}
+\alias{minmaxBias}
+\alias{minmaxBias-methods}
+\alias{minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method}
+\alias{minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}
+\alias{minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}
+\alias{minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method}
+
+\title{ Generic Function for the Computation of Bias-Optimally Robust ICs }
+\description{
+ Generic function for the computation of bias-optimally robust ICs
+ in case of infinitesimal robust models. This function is
+ rarely called directly.
+}
+\usage{
+minmaxBias(L2deriv, neighbor, biastype, ...)
+
+\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+\S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+\S4method{minmaxBias}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+\S4method{minmaxBias}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+}
+\arguments{
+ \item{L2deriv}{ L2-derivative of some L2-differentiable family
+ of probability measures. }
+ \item{neighbor}{ object of class \code{"Neighborhood"}. }
+ \item{biastype}{ object of class \code{"BiasType"}. }
+ \item{\dots}{ additional parameters. }
+ \item{Distr}{ object of class \code{"Distribution"}. }
+ \item{symm}{ logical: indicating symmetry of \code{L2deriv}. }
+ \item{DistrSymm}{ object of class \code{"DistributionSymmetry"}. }
+ \item{L2derivSymm}{ object of class \code{"FunSymmList"}. }
+ \item{L2derivDistrSymm}{ object of class \code{"DistrSymmList"}. }
+ \item{Finfo}{ Fisher information matrix. }
+ \item{z.start}{ initial value for the centering constant. }
+ \item{A.start}{ initial value for the standardizing matrix. }
+ \item{trafo}{ matrix: transformation of the parameter. }
+ \item{upper}{ upper bound for the optimal clipping bound. }
+ \item{maxiter}{ the maximum number of iterations. }
+ \item{tol}{ the desired accuracy (convergence tolerance).}
+ \item{warn}{ logical: print warnings. }
+}
+%\details{}
+\value{The bias-optimally robust IC is computed.}
+\section{Methods}{
+\describe{
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{
+ computes the bias optimal influence curve for symmetric bias for L2 differentiable
+ parametric families with unknown one-dimensional parameter. }
+
+ \item{L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+ biastype = "asymmetricBias"}{
+ computes the bias optimal influence curve for asymmetric bias for L2 differentiable
+ parametric families with unknown one-dimensional parameter. }
+
+ \item{L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+ biastype = "BiasType"}{
+ computes the bias optimal influence curve for symmetric bias for L2 differentiable
+ parametric families with unknown one-dimensional parameter. }
+
+ \item{L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+ biastype = "BiasType"}{
+ computes the bias optimal influence curve for symmetric bias for L2 differentiable
+ parametric families with unknown \eqn{k}-dimensional parameter
+ (\eqn{k > 1}) where the underlying distribution is univariate. }
+
+}}
+\references{
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+ Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+ Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+ Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+ Bayreuth: Dissertation.
+}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+ Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+%\note{}
+\seealso{\code{\link[RobAStBase]{InfRobModel-class}}}
+%\examples{}
+\concept{influence curve}
+\keyword{}
Deleted: pkg/ROptEst/man/oneStepEstimator.Rd
===================================================================
--- pkg/ROptEst/man/oneStepEstimator.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/oneStepEstimator.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,50 +0,0 @@
-\name{oneStepEstimator}
-\alias{oneStepEstimator}
-\alias{oneStepEstimator-methods}
-\alias{oneStepEstimator,numeric,InfluenceCurve,numeric-method}
-\alias{oneStepEstimator,numeric,InfluenceCurve,list-method}
-\alias{oneStepEstimator,matrix,InfluenceCurve,numeric-method}
-\alias{oneStepEstimator,matrix,InfluenceCurve,list-method}
-
-\title{Generic function for the computation of one-step estimators}
-\description{
- Generic function for the computation of one-step estimators.
-}
-\usage{
-oneStepEstimator(x, IC, start)
-}
-\arguments{
- \item{x}{ sample }
- \item{IC}{ object of class \code{"InfluenceCurve"} }
- \item{start}{ initial estimate }
-}
-\details{
- Given an initial estimation \code{start}, a sample \code{x}
- and an influence curve \code{IC} the corresponding one-step
- estimator is computed
-}
-\value{The one-step estimation is computed.}
-\section{Methods}{
-\describe{
- \item{x = "numeric", IC = "InfluenceCurve", start = "numeric"}{
- univariate samples. }
- \item{x = "numeric", IC = "InfluenceCurve", start = "list"}{
- univariate samples. }
- \item{x = "matrix", IC = "InfluenceCurve", start = "numeric"}{
- multivariate samples. }
- \item{x = "matrix", IC = "InfluenceCurve", start = "list"}{
- multivariate samples. }
-}}
-\references{
- Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{InfluenceCurve-class}}}
-%\examples{}
-\concept{one-step estimator}
-\concept{estimator}
-\keyword{}
Modified: pkg/ROptEst/man/optIC.Rd
===================================================================
--- pkg/ROptEst/man/optIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/optIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -15,11 +15,13 @@
\S4method{optIC}{L2ParamFamily,asCov}(model, risk)
-\S4method{optIC}{InfRobModel,asRisk}(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
+\S4method{optIC}{InfRobModel,asRisk}(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
-\S4method{optIC}{InfRobModel,asUnOvShoot}(model, risk, upper = 1e4, maxiter = 50,
- tol = .Machine$double.eps^0.4, warn = TRUE)
+\S4method{optIC}{InfRobModel,asUnOvShoot}(model, risk, biastype = symmetricBias(),
+ upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE)
\S4method{optIC}{FixRobModel,fiUnOvShoot}(model, risk, sampleSize, upper = 1e4, maxiter = 50,
tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
@@ -28,6 +30,7 @@
\item{model}{ probability model. }
\item{risk}{ object of class \code{"RiskType"}. }
\item{\dots}{ additional parameters. }
+ \item{biastype}{ object of class \code{"BiasType"} }
\item{z.start}{ initial value for the centering constant. }
\item{A.start}{ initial value for the standardizing matrix. }
\item{upper}{ upper bound for the optimal clipping bound. }
@@ -77,7 +80,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{InfluenceCurve-class}}, \code{\link{RiskType-class}}}
+\seealso{\code{\link[RobAStBase]{InfluenceCurve-class}}, \code{\link[distrMod]{RiskType-class}}}
\examples{
B <- BinomFamily(size = 25, prob = 0.25)
Modified: pkg/ROptEst/man/optRisk.Rd
===================================================================
--- pkg/ROptEst/man/optRisk.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/optRisk.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -13,9 +13,12 @@
\usage{
optRisk(model, risk, ...)
-\S4method{optRisk}{InfRobModel,asRisk}(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
- maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+\S4method{optRisk}{L2ParamFamily,asCov}(model, risk)
+\S4method{optRisk}{InfRobModel,asRisk}(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
\S4method{optRisk}{FixRobModel,fiUnOvShoot}(model, risk, sampleSize, upper = 1e4, maxiter = 50,
tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
}
@@ -23,6 +26,7 @@
\item{model}{ probability model }
\item{risk}{ object of class \code{RiskType} }
\item{\dots}{ additional parameters }
+ \item{biastype}{ object of class \code{BiasType} }
\item{z.start}{ initial value for the centering constant. }
\item{A.start}{ initial value for the standardizing matrix. }
\item{upper}{ upper bound for the optimal clipping bound. }
@@ -64,7 +68,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{RiskType-class}}}
+\seealso{\code{\link[distrMod]{RiskType-class}}}
\examples{
optRisk(model = NormLocationScaleFamily(), risk = asCov())
}
Modified: pkg/ROptEst/man/radiusMinimaxIC.Rd
===================================================================
--- pkg/ROptEst/man/radiusMinimaxIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/radiusMinimaxIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -10,7 +10,8 @@
\usage{
radiusMinimaxIC(L2Fam, neighbor, risk, ...)
-\S4method{radiusMinimaxIC}{L2ParamFamily,UncondNeighborhood,asGRisk}(L2Fam, neighbor, risk,
+\S4method{radiusMinimaxIC}{L2ParamFamily,UncondNeighborhood,asGRisk}(
+ L2Fam, neighbor, risk, biastype = symmetricBias(),
loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
}
@@ -19,6 +20,7 @@
\item{neighbor}{ object of class \code{"Neighborhood"}. }
\item{risk}{ object of class \code{"RiskType"}. }
\item{\dots}{ additional parameters. }
+ \item{biastype}{ object of class \code{"BiasType"}. }
\item{loRad}{ the lower end point of the interval to be searched. }
\item{upRad}{ the upper end point of the interval to be searched. }
\item{z.start}{ initial value for the centering constant. }
@@ -45,7 +47,8 @@
Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
Bayreuth: Dissertation.
}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
+\author{Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
%\note{}
\seealso{\code{\link{radiusMinimaxIC}}}
\examples{
Deleted: pkg/ROptEst/man/trAsCov-class.Rd
===================================================================
--- pkg/ROptEst/man/trAsCov-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/trAsCov-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,36 +0,0 @@
-\name{trAsCov-class}
-\docType{class}
-\alias{trAsCov-class}
-\title{Trace of asymptotic covariance}
-\description{Class of trace of asymptotic covariance.}
-\section{Objects from the Class}{
- Objects can be created by calls of the form \code{new("trAsCov", ...)}.
- More frequently they are created via the generating function
- \code{trAsCov}.
-}
-\section{Slots}{
- \describe{
- \item{\code{type}:}{Object of class \code{"character"}:
- \dQuote{trace of asymptotic covariance}. }
- }
-}
-\section{Extends}{
-Class \code{"asRisk"}, directly.\cr
-Class \code{"RiskType"}, by class \code{"asRisk"}.
-}
-%\section{Methods}{}
-\references{
- Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{asRisk-class}}, \code{\link{trAsCov}}}
-\examples{
-new("trAsCov")
-}
-\concept{asymptotic covariance}
-\concept{risk}
-\keyword{classes}
Deleted: pkg/ROptEst/man/trAsCov.Rd
===================================================================
--- pkg/ROptEst/man/trAsCov.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/trAsCov.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,27 +0,0 @@
-\name{trAsCov}
-\alias{trAsCov}
-\title{Generating function for trAsCov-class}
-\description{
- Generates an object of class \code{"trAsCov"}.
-}
-\usage{trAsCov()}
-%\details{}
-\value{Object of class \code{"trAsCov"}}
-\references{
- Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
-
- Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
- Bayreuth: Dissertation.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{trAsCov-class}}}
-\examples{
-trAsCov()
-
-## The function is currently defined as
-function(){ new("trAsCov") }
-}
-\concept{asymptotic covariance}
-\concept{risk}
-\keyword{}
Deleted: pkg/ROptEst/man/trFiCov-class.Rd
===================================================================
--- pkg/ROptEst/man/trFiCov-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/trFiCov-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,35 +0,0 @@
-\name{trFiCov-class}
-\docType{class}
-\alias{trFiCov-class}
-
-\title{Trace of finite-sample covariance}
-\description{Class of trace of finite-sample covariance.}
-\section{Objects from the Class}{
- Objects can be created by calls of the form \code{new("trFiCov", ...)}.
- More frequently they are created via the generating function
- \code{trFiCov}.
-}
-\section{Slots}{
- \describe{
- \item{\code{type}:}{Object of class \code{"character"}:
- \dQuote{trace of finite-sample covariance}. }
- }
-}
-\section{Extends}{
-Class \code{"fiRisk"}, directly.\cr
-Class \code{"RiskType"}, by class \code{"fiRisk"}.
-}
-%\section{Methods}{}
-\references{
- Ruckdeschel, P. and Kohl, M. (2005) How to approximate
- the finite sample risk of M-estimators.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{fiRisk-class}}, \code{\link{trFiCov}}}
-\examples{
-new("trFiCov")
-}
-\concept{finite-sample covariance}
-\concept{risk}
-\keyword{classes}
Deleted: pkg/ROptEst/man/trFiCov.Rd
===================================================================
--- pkg/ROptEst/man/trFiCov.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/ROptEst/man/trFiCov.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,25 +0,0 @@
-\name{trFiCov}
-\alias{trFiCov}
-\title{Generating function for trFiCov-class}
-\description{
- Generates an object of class \code{"trFiCov"}.
-}
-\usage{trFiCov()}
-%\details{}
-\value{Object of class \code{"trFiCov"}}
-\references{
- Ruckdeschel, P. and Kohl, M. (2005) How to approximate
- the finite sample risk of M-estimators.
-}
-\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
-%\note{}
-\seealso{\code{\link{trFiCov-class}}}
-\examples{
-trFiCov()
-
-## The function is currently defined as
-function(){ new("trFiCov") }
-}
-\concept{finite-sample covariance}
-\concept{risk}
-\keyword{}
Added: pkg/ROptEst.Rcheck/00check.log
===================================================================
--- pkg/ROptEst.Rcheck/00check.log (rev 0)
+++ pkg/ROptEst.Rcheck/00check.log 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,56 @@
+* using log directory 'C:/rtest/RobASt/pkg/ROptEst.Rcheck'
+* using R version 2.6.0 RC (2007-10-01 r43043)
+* checking for file 'ROptEst/DESCRIPTION' ... OK
+* this is package 'ROptEst' version '0.6.0'
+* checking package name space information ... OK
+* checking package dependencies ... OK
+* checking if this is a source package ... OK
+* checking whether package 'ROptEst' can be installed ... WARNING
+Found the following significant warnings:
+ Warning: package 'distr' was built under R version 2.6.1
+See 'C:/rtest/RobASt/pkg/ROptEst.Rcheck/00install.out' for details.
+* checking package directory ... OK
+* checking for portable file names ... OK
+* checking DESCRIPTION meta-information ... OK
+* checking top-level files ... OK
+* checking index information ... OK
+* checking package subdirectories ... OK
+* checking R files for non-ASCII characters ... OK
+* checking R files for syntax errors ... OK
+* checking whether the package can be loaded ... OK
+* checking whether the package can be loaded with stated dependencies ... OK
+* checking whether the name space can be loaded with stated dependencies ... OK
+* checking for unstated dependencies in R code ... OK
+* checking S3 generic/method consistency ... OK
+* checking replacement functions ... OK
+* checking foreign function calls ... OK
+* checking R code for possible problems ... OK
+* checking Rd files ... OK
+* checking Rd cross-references ... OK
+* checking for missing documentation entries ... OK
+* checking for code/documentation mismatches ... OK
+* checking Rd \usage sections ... OK
+* creating ROptEst-Ex.R ... OK
+* checking examples ... ERROR
+Running examples in 'ROptEst-Ex.R' failed.
+The error most likely occurred in:
+
+> ### * leastFavorableRadius
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: leastFavorableRadius
+> ### Title: Generic Function for the Computation of Least Favorable Radii
+> ### Aliases: leastFavorableRadius leastFavorableRadius-methods
+> ### leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method
+>
+>
+> ### ** Examples
+>
+> N <- NormLocationFamily(mean=0, sd=1)
+> leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
++ risk=asMSE(), rho=0.5)
+Fehler in uniroot(getIneffDiff, lower = lower, upper = upper, tol = .Machine$double.eps^0.25, :
+ f() values at end points not of opposite sign
+Calls: leastFavorableRadius ... leastFavorableRadius -> .local -> optimize -> <Anonymous> -> f -> uniroot
+Ausführung angehalten
Added: pkg/ROptEst.Rcheck/00install.out
===================================================================
--- pkg/ROptEst.Rcheck/00install.out (rev 0)
+++ pkg/ROptEst.Rcheck/00install.out 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,95 @@
+installing R.css in C:/rtest/RobASt/pkg/ROptEst.Rcheck
+
+
+---------- Making package ROptEst ------------
+ adding build stamp to DESCRIPTION
+ installing NAMESPACE file and metadata
+ installing R files
+ installing inst files
+ preparing package ROptEst for lazy loading
+Loading required package: distr
+Warning: package 'distr' was built under R version 2.6.1
+Loading required package: startupmsg
+:startupmsg> Utilities for start-up messages (version 0.5)
+
+:startupmsg> For more information see ?"startupmsg", NEWS("startupmsg")
+:startupmsg>
+
+:distr> Object orientated implementation of distributions (version 2.0)
+
+:distr> Attention: Arithmetics on distribution objects are understood as
+:distr> operations on corresponding random variables (r.v.s); see distrARITH().
+:distr> Some functions from package 'stats' are intentionally masked
+:distr> ---see distrMASK().
+:distr> Note that global options are controlled by distroptions()
+:distr> ---c.f. ?"distroptions".
+
+:distr> For more information see ?"distr", NEWS("distr"), as well as
+:distr> http://distr.r-forge.r-project.org/
+:distr> Package "distrDoc" provides a vignette to this package as well as
+:distr> to several extension packages; try vignette("distr").
+:distr>
+
+Loading required package: distrEx
+Loading required package: evd
+:distrEx> Extensions of package distr (version 2.0)
+
+:distrEx> Note: Packages "e1071", "moments", "fBasics" should be attached
+:distrEx> /before/ package "distrEx". See distrExMASK().
+
+:distrEx> For more information see ?"distrEx", NEWS("distrEx"), as well as
+:distrEx> http://distr.r-forge.r-project.org/
+:distrEx> Package "distrDoc" provides a vignette to this package as well as
+:distrEx> to several related packages; try vignette("distr").
+:distrEx>
+
+Loading required package: distrMod
+Loading required package: RandVar
+:RandVar> Implementation of random variables (version 0.6.2)
+
+:RandVar> For more information see ?"RandVar", as well as
+:RandVar>
+:RandVar> http://www.uni-bayreuth.de/departments/math/org/mathe7/DISTR/RandVar.html
+:RandVar> This package also includes a vignette; try vignette("RandVar").
+:RandVar>
+
+:distrMod> Object orientated implementation of probability models (version 2.0)
+
+:distrMod> For more information see ?"distrMod", as well as
+:distrMod> http://distr.r-forge.r-project.org/
+:distrMod> Package "distrDoc" provides a vignette to this package as well as
+:distrMod> to several related packages; try vignette("distr").
+:distrMod>
+
+Loading required package: RobAStBase
+ installing man source files
+ installing indices
+ installing help
+ >>> Building/Updating help pages for package 'ROptEst'
+ Formats: text html latex example chm
+ getAsRisk text html latex
+ getBiasIC text html latex
+ getFiRisk text html latex
+ getFixClip text html latex
+ getFixRobIC text html latex
+ getIneffDiff text html latex
+ getInfCent text html latex
+ getInfClip text html latex
+ getInfGamma text html latex
+ getInfRobIC text html latex
+ getInfStand text html latex
+ getL1normL2deriv text html latex example
+ getL2normL2deriv text html latex example
+ getRiskIC text html latex
+ leastFavorableRadius text html latex example
+ locMEstimator text html latex
+ lowerCaseRadius text html latex example
+ minmaxBias text html latex
+ optIC text html latex example
+ optRisk text html latex example
+ radiusMinimaxIC text html latex example
+ trAsCov-class text html latex example
+ trFiCov-class text html latex example
+ adding MD5 sums
+
+* DONE (ROptEst)
Added: pkg/ROptEst.Rcheck/R.css
===================================================================
--- pkg/ROptEst.Rcheck/R.css (rev 0)
+++ pkg/ROptEst.Rcheck/R.css 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,37 @@
+BODY{ background: white;
+ color: black }
+
+A:link{ background: white;
+ color: blue }
+A:visited{ background: white;
+ color: rgb(50%, 0%, 50%) }
+
+H1{ background: white;
+ color: rgb(55%, 55%, 55%);
+ font-family: monospace;
+ font-size: x-large;
+ text-align: center }
+
+H2{ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+ font-size: large;
+ text-align: center }
+
+H3{ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace;
+ font-size: large }
+
+IMG.toplogo{ vertical-align: middle }
+
+IMG.arrow{ width: 30;
+ height: 30;
+ border: 0 }
+
+span.acronym{font-size: small}
+span.env{font-family: monospace}
+span.file{font-family: monospace}
+span.option{font-family: monospace}
+span.pkg{font-weight: bold}
+span.samp{font-family: monospace}
Added: pkg/ROptEst.Rcheck/ROptEst/CONTENTS
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/CONTENTS (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/CONTENTS 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,137 @@
+Entry: getAsRisk
+Aliases: getAsRisk getAsRisk-methods getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method
+Keywords:
+Description: Generic Function for Computation of Asymptotic Risks
+URL: ../../../library/ROptEst/html/getAsRisk.html
+
+Entry: getBiasIC
+Aliases: getBiasIC getBiasIC-methods getBiasIC,IC,ContNeighborhood,missing,BiasType-method getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method
+Keywords:
+Description: Generic function for the computation of the asymptotic bias for an IC
+URL: ../../../library/ROptEst/html/getBiasIC.html
+
+Entry: getFiRisk
+Aliases: getFiRisk getFiRisk-methods getFiRisk,fiUnOvShoot,Norm,ContNeighborhood-method getFiRisk,fiUnOvShoot,Norm,TotalVarNeighborhood-method
+Keywords:
+Description: Generic Function for Computation of Finite-Sample Risks
+URL: ../../../library/ROptEst/html/getFiRisk.html
+
+Entry: getFixClip
+Aliases: getFixClip getFixClip-methods getFixClip,numeric,Norm,fiUnOvShoot,ContNeighborhood-method getFixClip,numeric,Norm,fiUnOvShoot,TotalVarNeighborhood-method
+Keywords:
+Description: Generic Function for the Computation of the Optimal Clipping Bound
+URL: ../../../library/ROptEst/html/getFixClip.html
+
+Entry: getFixRobIC
+Aliases: getFixRobIC getFixRobIC-methods getFixRobIC,Norm,fiUnOvShoot,UncondNeighborhood-method
+Keywords:
+Description: Generic Function for the Computation of Optimally Robust ICs
+URL: ../../../library/ROptEst/html/getFixRobIC.html
+
+Entry: getIneffDiff
+Aliases: getIneffDiff getIneffDiff-methods getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method
+Keywords:
+Description: Generic Function for the Computation of Inefficiency Differences
+URL: ../../../library/ROptEst/html/getIneffDiff.html
+
+Entry: getInfCent
+Aliases: getInfCent getInfCent-methods getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getInfCent,RealRandVariable,ContNeighborhood,BiasType-method getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method
+Keywords:
+Description: Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound
+URL: ../../../library/ROptEst/html/getInfCent.html
+
+Entry: getInfClip
+Aliases: getInfClip getInfClip-methods getInfClip,numeric,UnivariateDistribution,asMSE,ContNeighborhood-method getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood-method getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method
+Keywords:
+Description: Generic Function for the Computation of the Optimal Clipping Bound
+URL: ../../../library/ROptEst/html/getInfClip.html
+
+Entry: getInfGamma
+Aliases: getInfGamma getInfGamma-methods getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method
+Keywords:
+Description: Generic Function for the Computation of the Optimal Clipping Bound
+URL: ../../../library/ROptEst/html/getInfGamma.html
+
+Entry: getInfRobIC
+Aliases: getInfRobIC getInfRobIC-methods getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method
+Keywords:
+Description: Generic Function for the Computation of Optimally Robust ICs
+URL: ../../../library/ROptEst/html/getInfRobIC.html
+
+Entry: getInfStand
+Aliases: getInfStand getInfStand-methods getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getInfStand,RealRandVariable,ContNeighborhood,BiasType-method getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method
+Keywords:
+Description: Generic Function for the Computation of the Standardizing Matrix
+URL: ../../../library/ROptEst/html/getInfStand.html
+
+Entry: getL1normL2deriv
+Aliases: getL1normL2deriv getL1normL2deriv-methods getL1normL2deriv,UnivariateDistribution-method getL1normL2deriv,RealRandVariable-method
+Keywords:
+Description: Calculation of L1 norm of L2derivative
+URL: ../../../library/ROptEst/html/getL1normL2deriv.html
+
+Entry: getL2normL2deriv
+Aliases: getL2normL2deriv
+Keywords:
+Description: Calculation of L2 norm of L2derivative
+URL: ../../../library/ROptEst/html/getL2normL2deriv.html
+
+Entry: getRiskIC
+Aliases: getRiskIC getRiskIC-methods getRiskIC,IC,asCov,missing,missing-method getRiskIC,IC,asCov,missing,L2ParamFamily-method getRiskIC,IC,trAsCov,missing,missing-method getRiskIC,IC,trAsCov,missing,L2ParamFamily-method getRiskIC,IC,asBias,UncondNeighborhood,missing-method getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method getRiskIC,IC,asMSE,UncondNeighborhood,missing-method getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method
+Keywords:
+Description: Generic function for the computation of a risk for an IC
+URL: ../../../library/ROptEst/html/getRiskIC.html
+
+Entry: leastFavorableRadius
+Aliases: leastFavorableRadius leastFavorableRadius-methods leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method
+Keywords:
+Description: Generic Function for the Computation of Least Favorable Radii
+URL: ../../../library/ROptEst/html/leastFavorableRadius.html
+
+Entry: locMEstimator
+Aliases: locMEstimator locMEstimator-methods locMEstimator,numeric,InfluenceCurve-method
+Keywords:
+Description: Generic function for the computation of location M estimators
+URL: ../../../library/ROptEst/html/locMEstimator.html
+
+Entry: lowerCaseRadius
+Aliases: lowerCaseRadius lowerCaseRadius-methods lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method
+Keywords:
+Description: Computation of the lower case radius
+URL: ../../../library/ROptEst/html/lowerCaseRadius.html
+
+Entry: minmaxBias
+Aliases: minmaxBias minmaxBias-methods minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method
+Keywords:
+Description: Generic Function for the Computation of Bias-Optimally Robust ICs
+URL: ../../../library/ROptEst/html/minmaxBias.html
+
+Entry: optIC
+Aliases: optIC optIC-methods optIC,L2ParamFamily,asCov-method optIC,InfRobModel,asRisk-method optIC,InfRobModel,asUnOvShoot-method optIC,FixRobModel,fiUnOvShoot-method
+Keywords:
+Description: Generic function for the computation of optimally robust ICs
+URL: ../../../library/ROptEst/html/optIC.html
+
+Entry: optRisk
+Aliases: optRisk optRisk-methods optRisk,L2ParamFamily,asCov-method optRisk,InfRobModel,asRisk-method optRisk,FixRobModel,fiUnOvShoot-method
+Keywords:
+Description: Generic function for the computation of the minimal risk
+URL: ../../../library/ROptEst/html/optRisk.html
+
+Entry: radiusMinimaxIC
+Aliases: radiusMinimaxIC radiusMinimaxIC-methods radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method
+Keywords:
+Description: Generic function for the computation of the radius minimax IC
+URL: ../../../library/ROptEst/html/radiusMinimaxIC.html
+
+Entry: trAsCov-class
+Aliases: trAsCov-class
+Keywords: classes
+Description: Trace of asymptotic covariance
+URL: ../../../library/ROptEst/html/trAsCov-class.html
+
+Entry: trFiCov-class
+Aliases: trFiCov-class
+Keywords: classes
+Description: Trace of finite-sample covariance
+URL: ../../../library/ROptEst/html/trFiCov-class.html
Added: pkg/ROptEst.Rcheck/ROptEst/DESCRIPTION
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/DESCRIPTION (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/DESCRIPTION 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,15 @@
+Package: ROptEst
+Version: 0.6.0
+Date: 2008-02-14
+Title: Optimally robust estimation
+Description: Optimally robust estimation using S4 classes and methods
+Depends: R(>= 2.4.0), methods, distr(>= 2.0), distrEx(>= 2.0),
+ distrMod(>= 2.0), RandVar(>= 0.6.2), RobAStBase
+Author: Matthias Kohl
+Maintainer: Matthias Kohl <Matthias.Kohl at stamats.de>
+SaveImage: no
+LazyLoad: yes
+License: GPL version 2 or later
+URL: http://www.stamats.de/RobASt.htm
+Packaged: Thu Jan 3 20:00:08 2008; btm722
+Built: R 2.6.0; ; 2008-02-16 04:20:23; windows
Added: pkg/ROptEst.Rcheck/ROptEst/INDEX
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/INDEX (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/INDEX 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,41 @@
+getAsRisk Generic Function for Computation of Asymptotic
+ Risks
+getBiasIC Generic function for the computation of the
+ asymptotic bias for an IC
+getFiRisk Generic Function for Computation of
+ Finite-Sample Risks
+getFixClip Generic Function for the Computation of the
+ Optimal Clipping Bound
+getFixRobIC Generic Function for the Computation of
+ Optimally Robust ICs
+getIneffDiff Generic Function for the Computation of
+ Inefficiency Differences
+getInfCent Generic Function for the Computation of the
+ Optimal Centering Constant/Lower Clipping Bound
+getInfClip Generic Function for the Computation of the
+ Optimal Clipping Bound
+getInfGamma Generic Function for the Computation of the
+ Optimal Clipping Bound
+getInfRobIC Generic Function for the Computation of
+ Optimally Robust ICs
+getInfStand Generic Function for the Computation of the
+ Standardizing Matrix
+getL1normL2deriv Calculation of L1 norm of L2derivative
+getL2normL2deriv Calculation of L2 norm of L2derivative
+getRiskIC Generic function for the computation of a risk
+ for an IC
+leastFavorableRadius Generic Function for the Computation of Least
+ Favorable Radii
+locMEstimator Generic function for the computation of
+ location M estimators
+lowerCaseRadius Computation of the lower case radius
+minmaxBias Generic Function for the Computation of
+ Bias-Optimally Robust ICs
+optIC Generic function for the computation of
+ optimally robust ICs
+optRisk Generic function for the computation of the
+ minimal risk
+radiusMinimaxIC Generic function for the computation of the
+ radius minimax IC
+trAsCov-class Trace of asymptotic covariance
+trFiCov-class Trace of finite-sample covariance
Added: pkg/ROptEst.Rcheck/ROptEst/MD5
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/MD5 (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/MD5 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,103 @@
+f9ce718a11b2a4c3047bf290b998297a *CONTENTS
+651f38a87af3b5cb74d08103cce57d43 *DESCRIPTION
+408153d3785bd10f84830a1010678d69 *INDEX
+76b39e9bf73081a502fa1fd122482669 *Meta/Rd.rds
+b8500c64689fa30ccf47d8f5ed9ea43c *Meta/hsearch.rds
+3e2b0372a9fae49e1c1dc24cf607c0ba *Meta/nsInfo.rds
+a34606f0db123b3a9c569776fc083ad3 *Meta/package.rds
+296b7c0957025759d8894bf8f59ecd18 *NAMESPACE
+b68c9fc90e93c5795e4cd69c33064a0f *R-ex/getL1normL2deriv.R
+d57b08bb15c0c26198d5f40b8f61e215 *R-ex/getL2normL2deriv.R
+aa2d600db304a4d2d9f1e33045186374 *R-ex/leastFavorableRadius.R
+2bd67fed5d859b73ab17fb20f8a71225 *R-ex/lowerCaseRadius.R
+58597007cabe56ac5f856d1546918d8e *R-ex/optIC.R
+57450e0ae907e5429ff224f5d7e74887 *R-ex/optRisk.R
+7cad0fe9e65bd87ff41e4eb79db7fed4 *R-ex/radiusMinimaxIC.R
+9dc46a82aafe3a4ff25b23fe52d8b04f *R-ex/trAsCov-class.R
+6e8e004dcc5d48a8a465019db94c7852 *R-ex/trFiCov-class.R
+f07d3015c4220dea7a7be8c741d2985b *R/ROptEst
+3049004d7a05c633e67545a78780e3b1 *R/ROptEst.rdb
+1982f8d9fd3eb278263e9aef7c2ba52c *R/ROptEst.rdx
+a5be677b35911a9b59806d508f02df1c *chtml/ROptEst.chm
+476a67aaf857d17aed50c3ff72ded876 *help/AnIndex
+d908ca5d8ccf1dc99eaf2d6b0fd77439 *help/getAsRisk
+40f1e536f41a3c4ecfd4809a83c1de59 *help/getBiasIC
+28d469e354ca6e77caad3923f427153f *help/getFiRisk
+c26e7baca9a852a0d81742c2f6fa8589 *help/getFixClip
+3659ae88106d926dfc8bad09f030ed51 *help/getFixRobIC
+3d037baf98c5140664dbd48c40ce5ae9 *help/getIneffDiff
+1ce8eff5d0ab3267d6db78b0bd55c4a6 *help/getInfCent
+8893acef194bdd2ea0f203fe75887d75 *help/getInfClip
+bd3656062cbeb9184b24bb7c847a51d5 *help/getInfGamma
+93b6532b7c958851ba523b8b693d3b99 *help/getInfRobIC
+6d9df10d8d3cc23321b03f7606e69c62 *help/getInfStand
+b8c86efff274a449735b58747f6826e1 *help/getL1normL2deriv
+c8fcb0db845ccbf35cf66bed6e96858c *help/getL2normL2deriv
+fa76987d976c123a7c2124eb81b39bfa *help/getRiskIC
+2c27ed4c8384b8e53362f8107087d16b *help/leastFavorableRadius
+8c01a631102fdd1f77f6222b9f8ddf70 *help/locMEstimator
+187a5b6260072d46352f7911f2906239 *help/lowerCaseRadius
+041de47dc87a1468f67b4dbb2b68cdb0 *help/minmaxBias
+2be4f9ae74d393b6f2ca24c0309fca0b *help/optIC
+97dc707ccd5f066b6ca719562bede012 *help/optRisk
+4753f028a0c3bca0b64d483298432e35 *help/radiusMinimaxIC
+3f42d198c975188a1a9109f778d720b1 *help/trAsCov-class
+7a7ea36507f7e3dc6eea5d5557ebb1c1 *help/trFiCov-class
+05f1f2f12632af749619b560b96e58cc *html/00Index.html
+6d3602ec8066e028c0881740d533a5ac *html/getAsRisk.html
+b3d6eee7f9a26406ea87864b5f3fa300 *html/getBiasIC.html
+9d27c4a9dc5e53d569128a043cb18a83 *html/getFiRisk.html
+99fe2b1f734df01cdcdb17d4edd2e0b0 *html/getFixClip.html
+2f118284991f85b196b5c637b86e8683 *html/getFixRobIC.html
+879eb96154fcb74fde512021522abc64 *html/getIneffDiff.html
+9047661d5c5b69892c9d146cfefee47d *html/getInfCent.html
+63240e6b893854e20471032ed02a51d0 *html/getInfClip.html
+dd2f2649b7187f51c29cbb56d5d9c88a *html/getInfGamma.html
+9561b9db5f97bccbb3fe572e6e3e3824 *html/getInfRobIC.html
+cada9c53fa31e7cd00ed033a381bad93 *html/getInfStand.html
+f4a5f2bf5f67f80c0f152de58c8ac477 *html/getL1normL2deriv.html
+9468041e936bb36524d37ab37bfeda36 *html/getL2normL2deriv.html
+164726a975c672fac6b1065a4afe5cd8 *html/getRiskIC.html
+80bb8b5580c63ffed7f17767797d61a8 *html/leastFavorableRadius.html
+c0019701c0769c949e6242f138614514 *html/locMEstimator.html
+85be97d6ec28927fa597b484b3642373 *html/lowerCaseRadius.html
+4ed45313140b4acda7cd4de536417d21 *html/minmaxBias.html
+33d74aee4fc6aa94929fa6b0b5d53efe *html/optIC.html
+eca7e11887cecd8dc91bfcadad944f59 *html/optRisk.html
+97960ecce9e23f095e501e7e2613b4d6 *html/radiusMinimaxIC.html
+17343cd0dba40394f433246901b35e77 *html/trAsCov-class.html
+827ce9a0ee675a2025fd657a2ba1bed9 *html/trFiCov-class.html
+95211ce890cab62ca5670210706988f1 *latex/getAsRisk.tex
+1e99e0a7342a3aad24b99e2ea05720bf *latex/getBiasIC.tex
+f8c284de9aacd3a6327d894f45936b50 *latex/getFiRisk.tex
+4a76245fc93d4ae5d17e706a86e4202e *latex/getFixClip.tex
+0fec0ab2d04b6ca5ea5ba877b9c5817f *latex/getFixRobIC.tex
+f07d9d0e4fdd46e907a18561331e398b *latex/getIneffDiff.tex
+d5852de975bae83848589097979db01e *latex/getInfCent.tex
+91abe5f5919de853f3d960fb2cadaf94 *latex/getInfClip.tex
+ef343fc5845892995bb0b1bd98738f2d *latex/getInfGamma.tex
+0e04eb7c9cbf0b621853672d60717825 *latex/getInfRobIC.tex
+bd6cf4339ef586c25271d102a0b9318b *latex/getInfStand.tex
+3be1f7ff7826f2b750604da5502cbfbc *latex/getL1normL2deriv.tex
+9717117df863d7945653aff08581756d *latex/getL2normL2deriv.tex
+81acfa31ae4c431e80557568ede4ada8 *latex/getRiskIC.tex
+e5d64338f7e6c0265b3d79366acf5c35 *latex/leastFavorableRadius.tex
+73b9e0f8c56e680fa0d17bfb9d54b581 *latex/locMEstimator.tex
+a3f0cd31362e1e9817988516680b16a8 *latex/lowerCaseRadius.tex
+a7f9c2f50719711b003543472ed4cfc9 *latex/minmaxBias.tex
+9f55cf37c10a3f377554732f12c204b3 *latex/optIC.tex
+4e5cd9f2c6f26cbc58a2841c864fe5e6 *latex/optRisk.tex
+82764afc3a5269bab734c124a595115f *latex/radiusMinimaxIC.tex
+5f24f9e0957769925ffb143a5a3a7787 *latex/trAsCov-class.tex
+963eb602c05d79f2dbd0fae4487f2ede *latex/trFiCov-class.tex
+f21ceade6a27ddf91b05165c7c963195 *man/ROptEst.Rd.gz
+d3969782e60258521d85e8b10c8d67be *scripts/BinomialModel.R
+aa72d6bf036b96c6c8c2c8d7bc518a12 *scripts/ExponentialScaleModel.R
+e08885b4745dd8889282819077d70134 *scripts/GammaModel.R
+7e4c5f532880fe3aa31a45b3ce55a859 *scripts/GumbelLocationModel.R
+97c7ab6aa16ccfe9af27fb5fa30df99f *scripts/LognormalAndNormalModel.R
+f5141d73332e64db02dde8825c55cdc7 *scripts/NormalLocationScaleModel.R
+431a7964d0d24031f448fa1a151da85f *scripts/NormalScaleModel.R
+c8b00bb62e7ce1033918b4aa6a6105b5 *scripts/PoissonModel.R
+456e07f39882c40c2752330244cbed9c *scripts/UnderOverShootRisk.R
+c515781b924069915fe74337ca4f5ef4 *tests/tests.R
Added: pkg/ROptEst.Rcheck/ROptEst/Meta/Rd.rds
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+ application/octet-stream
Added: pkg/ROptEst.Rcheck/ROptEst/Meta/nsInfo.rds
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+ application/octet-stream
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+ application/octet-stream
Added: pkg/ROptEst.Rcheck/ROptEst/NAMESPACE
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/NAMESPACE (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/NAMESPACE 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,55 @@
+import("distr")
+import("distrEx")
+import("distrMod")
+import("RobAStBase")
+import("RandVar")
+
+exportMethods("show",
+ "coerce",
+ "length")
+exportMethods("type",
+ "SymmCenter")
+exportMethods("name", "name<-",
+ "distribution",
+ "distrSymm",
+ "props", "props<-", "addProp<-",
+ "main", "main<-",
+ "nuisance", "nuisance<-",
+ "trafo", "trafo<-",
+ "param",
+ "infoPlot")
+exportMethods("radius")
+exportMethods("center", "center<-",
+ "neighbor", "neighbor<-")
+exportMethods("Curve",
+ "Risks", "Risks<-", "addRisk<-",
+ "Infos", "Infos<-", "addInfo<-",
+ "CallL2Fam", "CallL2Fam<-",
+ "generateIC",
+ "checkIC",
+ "evalIC",
+ "clip", "clip<-",
+ "cent", "cent<-",
+ "stand", "stand<-",
+ "lowerCase", "lowerCase<-",
+ "neighborRadius", "neighborRadius<-",
+ "clipLo", "clipLo<-",
+ "clipUp", "clipUp<-")
+exportMethods("optIC",
+ "getInfRobIC",
+ "getFixRobIC",
+ "getAsRisk",
+ "getFiRisk",
+ "getInfClip",
+ "getFixClip",
+ "getInfGamma",
+ "getInfCent",
+ "getInfStand",
+ "getRiskIC",
+ "optRisk",
+ "radiusMinimaxIC",
+ "getIneffDiff",
+ "leastFavorableRadius",
+ "lowerCaseRadius",
+ "minmaxBias", "getBiasIC", "getL1normL2deriv")
+export("getL2normL2deriv")
\ No newline at end of file
Added: pkg/ROptEst.Rcheck/ROptEst/R/ROptEst
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R/ROptEst (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R/ROptEst 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,9 @@
+local({
+ info <- loadingNamespaceInfo()
+ ns <- .Internal(getRegisteredNamespace(as.name(info$pkgname)))
+ if (is.null(ns))
+ stop("cannot find name space environment");
+ barepackage <- sub("([^-]+)_.*", "\\1", info$pkgname)
+ dbbase <- file.path(info$libname, info$pkgname, "R", barepackage)
+ lazyLoad(dbbase, ns, filter = function(n) n != ".__NAMESPACE__.")
+})
Added: pkg/ROptEst.Rcheck/ROptEst/R/ROptEst.rdb
===================================================================
(Binary files differ)
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___________________________________________________________________
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+ application/octet-stream
Added: pkg/ROptEst.Rcheck/ROptEst/R/ROptEst.rdx
===================================================================
(Binary files differ)
Property changes on: pkg/ROptEst.Rcheck/ROptEst/R/ROptEst.rdx
___________________________________________________________________
Name: svn:mime-type
+ application/octet-stream
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/getL1normL2deriv.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/getL1normL2deriv.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/getL1normL2deriv.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,13 @@
+### Name: getL1normL2deriv
+### Title: Calculation of L1 norm of L2derivative
+### Aliases: getL1normL2deriv getL1normL2deriv-methods
+### getL1normL2deriv,UnivariateDistribution-method
+### getL1normL2deriv,RealRandVariable-method
+
+
+### ** Examples
+
+##
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/getL2normL2deriv.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/getL2normL2deriv.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/getL2normL2deriv.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,11 @@
+### Name: getL2normL2deriv
+### Title: Calculation of L2 norm of L2derivative
+### Aliases: getL2normL2deriv
+
+
+### ** Examples
+
+##
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/leastFavorableRadius.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/leastFavorableRadius.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/leastFavorableRadius.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,14 @@
+### Name: leastFavorableRadius
+### Title: Generic Function for the Computation of Least Favorable Radii
+### Aliases: leastFavorableRadius leastFavorableRadius-methods
+### leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method
+
+
+### ** Examples
+
+N <- NormLocationFamily(mean=0, sd=1)
+leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5)
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/lowerCaseRadius.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/lowerCaseRadius.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/lowerCaseRadius.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,15 @@
+### Name: lowerCaseRadius
+### Title: Computation of the lower case radius
+### Aliases: lowerCaseRadius lowerCaseRadius-methods
+### lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method
+### lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-met
+### hod
+
+
+### ** Examples
+
+lowerCaseRadius(BinomFamily(size = 10), ContNeighborhood(), asMSE())
+lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/optIC.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/optIC.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/optIC.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,18 @@
+### Name: optIC
+### Title: Generic function for the computation of optimally robust ICs
+### Aliases: optIC optIC-methods optIC,L2ParamFamily,asCov-method
+### optIC,InfRobModel,asRisk-method optIC,InfRobModel,asUnOvShoot-method
+### optIC,FixRobModel,fiUnOvShoot-method
+
+
+### ** Examples
+
+B <- BinomFamily(size = 25, prob = 0.25)
+
+## classical optimal IC
+IC0 <- optIC(model = B, risk = asCov())
+plot(IC0) # plot IC
+checkIC(IC0, B)
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/optRisk.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/optRisk.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/optRisk.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,13 @@
+### Name: optRisk
+### Title: Generic function for the computation of the minimal risk
+### Aliases: optRisk optRisk-methods optRisk,L2ParamFamily,asCov-method
+### optRisk,InfRobModel,asRisk-method
+### optRisk,FixRobModel,fiUnOvShoot-method
+
+
+### ** Examples
+
+optRisk(model = NormLocationScaleFamily(), risk = asCov())
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/radiusMinimaxIC.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/radiusMinimaxIC.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/radiusMinimaxIC.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,14 @@
+### Name: radiusMinimaxIC
+### Title: Generic function for the computation of the radius minimax IC
+### Aliases: radiusMinimaxIC radiusMinimaxIC-methods
+### radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method
+
+
+### ** Examples
+
+N <- NormLocationFamily(mean=0, sd=1)
+radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5)
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/trAsCov-class.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/trAsCov-class.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/trAsCov-class.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,11 @@
+### Name: trAsCov-class
+### Title: Trace of asymptotic covariance
+### Aliases: trAsCov-class
+### Keywords: classes
+
+### ** Examples
+
+new("trAsCov")
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/R-ex/trFiCov-class.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/R-ex/trFiCov-class.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/R-ex/trFiCov-class.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,11 @@
+### Name: trFiCov-class
+### Title: Trace of finite-sample covariance
+### Aliases: trFiCov-class
+### Keywords: classes
+
+### ** Examples
+
+new("trFiCov")
+
+
+
Added: pkg/ROptEst.Rcheck/ROptEst/chtml/ROptEst.chm
===================================================================
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+ application/octet-stream
Added: pkg/ROptEst.Rcheck/ROptEst/help/AnIndex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/AnIndex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/AnIndex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,125 @@
+getAsRisk getAsRisk
+getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method getAsRisk
+getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method getAsRisk
+getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getAsRisk
+getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method getAsRisk
+getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method getAsRisk
+getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getAsRisk
+getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method getAsRisk
+getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method getAsRisk
+getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method getAsRisk
+getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method getAsRisk
+getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method getAsRisk
+getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method getAsRisk
+getAsRisk-methods getAsRisk
+getBiasIC getBiasIC
+getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method getBiasIC
+getBiasIC,IC,ContNeighborhood,missing,BiasType-method getBiasIC
+getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method getBiasIC
+getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method getBiasIC
+getBiasIC-methods getBiasIC
+getFiRisk getFiRisk
+getFiRisk,fiUnOvShoot,Norm,ContNeighborhood-method getFiRisk
+getFiRisk,fiUnOvShoot,Norm,TotalVarNeighborhood-method getFiRisk
+getFiRisk-methods getFiRisk
+getFixClip getFixClip
+getFixClip,numeric,Norm,fiUnOvShoot,ContNeighborhood-method getFixClip
+getFixClip,numeric,Norm,fiUnOvShoot,TotalVarNeighborhood-method getFixClip
+getFixClip-methods getFixClip
+getFixRobIC getFixRobIC
+getFixRobIC,Norm,fiUnOvShoot,UncondNeighborhood-method getFixRobIC
+getFixRobIC-methods getFixRobIC
+getIneffDiff getIneffDiff
+getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method getIneffDiff
+getIneffDiff-methods getIneffDiff
+getInfCent getInfCent
+getInfCent,RealRandVariable,ContNeighborhood,BiasType-method getInfCent
+getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method getInfCent
+getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method getInfCent
+getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method getInfCent
+getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getInfCent
+getInfCent-methods getInfCent
+getInfClip getInfClip
+getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood-method getInfClip
+getInfClip,numeric,UnivariateDistribution,asMSE,ContNeighborhood-method getInfClip
+getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method getInfClip
+getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method getInfClip
+getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method getInfClip
+getInfClip-methods getInfClip
+getInfGamma getInfGamma
+getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method getInfGamma
+getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method getInfGamma
+getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method getInfGamma
+getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method getInfGamma
+getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method getInfGamma
+getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method getInfGamma
+getInfGamma-methods getInfGamma
+getInfRobIC getInfRobIC
+getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method getInfRobIC
+getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method getInfRobIC
+getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method getInfRobIC
+getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method getInfRobIC
+getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method getInfRobIC
+getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method getInfRobIC
+getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method getInfRobIC
+getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method getInfRobIC
+getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method getInfRobIC
+getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method getInfRobIC
+getInfRobIC-methods getInfRobIC
+getInfStand getInfStand
+getInfStand,RealRandVariable,ContNeighborhood,BiasType-method getInfStand
+getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method getInfStand
+getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method getInfStand
+getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method getInfStand
+getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method getInfStand
+getInfStand-methods getInfStand
+getL1normL2deriv getL1normL2deriv
+getL1normL2deriv,RealRandVariable-method getL1normL2deriv
+getL1normL2deriv,UnivariateDistribution-method getL1normL2deriv
+getL1normL2deriv-methods getL1normL2deriv
+getL2normL2deriv getL2normL2deriv
+getRiskIC getRiskIC
+getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method getRiskIC
+getRiskIC,IC,asBias,UncondNeighborhood,missing-method getRiskIC
+getRiskIC,IC,asCov,missing,L2ParamFamily-method getRiskIC
+getRiskIC,IC,asCov,missing,missing-method getRiskIC
+getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method getRiskIC
+getRiskIC,IC,asMSE,UncondNeighborhood,missing-method getRiskIC
+getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method getRiskIC
+getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method getRiskIC
+getRiskIC,IC,trAsCov,missing,L2ParamFamily-method getRiskIC
+getRiskIC,IC,trAsCov,missing,missing-method getRiskIC
+getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method getRiskIC
+getRiskIC-methods getRiskIC
+leastFavorableRadius leastFavorableRadius
+leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method leastFavorableRadius
+leastFavorableRadius-methods leastFavorableRadius
+locMEstimator locMEstimator
+locMEstimator,numeric,InfluenceCurve-method locMEstimator
+locMEstimator-methods locMEstimator
+lowerCaseRadius lowerCaseRadius
+lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method lowerCaseRadius
+lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method lowerCaseRadius
+lowerCaseRadius-methods lowerCaseRadius
+minmaxBias minmaxBias
+minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method minmaxBias
+minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method minmaxBias
+minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method minmaxBias
+minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method minmaxBias
+minmaxBias-methods minmaxBias
+optIC optIC
+optIC,FixRobModel,fiUnOvShoot-method optIC
+optIC,InfRobModel,asRisk-method optIC
+optIC,InfRobModel,asUnOvShoot-method optIC
+optIC,L2ParamFamily,asCov-method optIC
+optIC-methods optIC
+optRisk optRisk
+optRisk,FixRobModel,fiUnOvShoot-method optRisk
+optRisk,InfRobModel,asRisk-method optRisk
+optRisk,L2ParamFamily,asCov-method optRisk
+optRisk-methods optRisk
+radiusMinimaxIC radiusMinimaxIC
+radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method radiusMinimaxIC
+radiusMinimaxIC-methods radiusMinimaxIC
+trAsCov-class trAsCov-class
+trFiCov-class trFiCov-class
Added: pkg/ROptEst.Rcheck/ROptEst/help/getAsRisk
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getAsRisk (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getAsRisk 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,170 @@
+getAsRisk package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _C_o_m_p_u_t_a_t_i_o_n _o_f _A_s_y_m_p_t_o_t_i_c _R_i_s_k_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of asymptotic risks. This
+ function is rarely called directly. It is used by other
+ functions.
+
+_U_s_a_g_e:
+
+ getAsRisk(risk, L2deriv, neighbor, biastype, ...)
+
+ ## S4 method for signature 'asMSE, UnivariateDistribution,
+ ## Neighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+ ## S4 method for signature 'asMSE, EuclRandVariable,
+ ## Neighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+ ## S4 method for signature 'asBias, UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
+
+ ## S4 method for signature 'asBias, UnivariateDistribution,
+ ## TotalVarNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
+
+ ## S4 method for signature 'asBias, RealRandVariable,
+ ## ContNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
+ z.start, A.start, maxiter, tol)
+
+ ## S4 method for signature 'asCov, UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+ ## S4 method for signature 'asCov, UnivariateDistribution,
+ ## TotalVarNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+ ## S4 method for signature 'asCov, RealRandVariable,
+ ## ContNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+
+ ## S4 method for signature 'trAsCov,
+ ## UnivariateDistribution, UncondNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+ ## S4 method for signature 'trAsCov, RealRandVariable,
+ ## ContNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+
+ ## S4 method for signature 'asUnOvShoot,
+ ## UnivariateDistribution, UncondNeighborhood, BiasType':
+ getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+ ## S4 method for signature 'asSemivar,
+ ## UnivariateDistribution, Neighborhood, onesidedBias':
+ getAsRisk(risk, L2deriv, neighbor, biastype,
+ clip, cent, stand, trafo)
+
+_A_r_g_u_m_e_n_t_s:
+
+ risk: object of class '"asRisk"'.
+
+ L2deriv: L2-derivative of some L2-differentiable family of probability
+ distributions.
+
+neighbor: object of class '"Neighborhood"'.
+
+biastype: object of class '"BiasType"'.
+
+ ...: additional parameters.
+
+ clip: optimal clipping bound.
+
+ cent: optimal centering constant.
+
+ stand: standardizing matrix.
+
+ trafo: matrix: transformation of the parameter.
+
+ Distr: object of class '"Distribution"'.
+
+L2derivDistrSymm: object of class '"DistrSymmList"'.
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ maxiter: the maximum number of iterations
+
+ tol: the desired accuracy (convergence tolerance).
+
+_V_a_l_u_e:
+
+ The asymptotic risk is computed.
+
+_M_e_t_h_o_d_s:
+
+ _r_i_s_k = "_a_s_M_S_E", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes asymptotic mean square error in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_M_S_E", _L_2_d_e_r_i_v = "_E_u_c_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes asymptotic mean square error in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_B_i_a_s", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes standardized asymptotic bias in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_B_i_a_s", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes standardized asymptotic bias in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_B_i_a_s", _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes standardized asymptotic bias in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_C_o_v", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes asymptotic covariance in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_C_o_v", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes asymptotic covariance in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_C_o_v", _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes asymptotic covariance in methods for function
+ 'getInfRobIC'.
+
+ _r_i_s_k = "_t_r_A_s_C_o_v", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes trace of asymptotic covariance in methods for
+ function 'getInfRobIC'.
+
+ _r_i_s_k = "_t_r_A_s_C_o_v", _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes trace of asymptotic covariance in methods for
+ function 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_U_n_O_v_S_h_o_o_t", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes asymptotic under-/overshoot risk in methods for
+ function 'getInfRobIC'.
+
+ _r_i_s_k = "_a_s_S_e_m_i_v_a_r", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_o_n_e_s_i_d_e_d_B_i_a_s":
+ computes asymptotic semivariance in methods for function
+ 'getInfRobIC'.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+ General Loss Functions. Statistics & Decisions (submitted).
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'asRisk-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getBiasIC
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getBiasIC (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getBiasIC 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,100 @@
+getBiasIC package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _a_s_y_m_p_t_o_t_i_c _b_i_a_s _f_o_r _a_n _I_C
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the asymptotic bias for an
+ IC.
+
+_U_s_a_g_e:
+
+ getBiasIC(IC, neighbor, L2Fam, biastype, ...)
+
+ ## S4 method for signature 'IC, ContNeighborhood, missing,
+ ## BiasType':
+ getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, ContNeighborhood,
+ ## L2ParamFamily, BiasType':
+ getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, TotalVarNeighborhood,
+ ## missing, BiasType':
+ getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, TotalVarNeighborhood,
+ ## L2ParamFamily, BiasType':
+ getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+_A_r_g_u_m_e_n_t_s:
+
+ IC: object of class '"InfluenceCurve"'
+
+neighbor: object of class '"Neighborhood"'.
+
+ L2Fam: object of class '"L2ParamFamily"'.
+
+biastype: object of class '"BiasType"'.
+
+ ...: additional parameters
+
+ tol: the desired accuracy (convergence tolerance).
+
+_D_e_t_a_i_l_s:
+
+ To make sure that the results are valid, it is recommended to
+ include an additional check of the IC properties of 'IC' using
+ 'checkIC'.
+
+_V_a_l_u_e:
+
+ The asymptotic bias of an IC is computed.
+
+_M_e_t_h_o_d_s:
+
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ asymptotic bias of 'IC' in case of convex contamination
+ neighborhoods and symmetric bias.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ asymptotic bias of 'IC' under 'L2Fam' in case of convex
+ contamination neighborhoods and symmetric bias.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ asymptotic bias of 'IC' in case of total variation
+ neighborhoods and symmetric bias.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ asymptotic bias of 'IC' under 'L2Fam' in case of total
+ variation neighborhoods and symmetric bias.
+
+_N_o_t_e:
+
+ This generic function is still under construction.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+_S_e_e _A_l_s_o:
+
+ 'getRiskIC-methods', 'InfRobModel-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getFiRisk
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getFiRisk (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getFiRisk 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,83 @@
+getFiRisk package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _C_o_m_p_u_t_a_t_i_o_n _o_f _F_i_n_i_t_e-_S_a_m_p_l_e _R_i_s_k_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of finite-sample risks. This
+ function is rarely called directly. It is used by other
+ functions.
+
+_U_s_a_g_e:
+
+ getFiRisk(risk, Distr, neighbor, ...)
+
+ ## S4 method for signature 'fiUnOvShoot, Norm,
+ ## ContNeighborhood':
+ getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
+
+ ## S4 method for signature 'fiUnOvShoot, Norm,
+ ## TotalVarNeighborhood':
+ getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
+
+_A_r_g_u_m_e_n_t_s:
+
+ risk: object of class '"RiskType"'.
+
+ Distr: object of class '"Distribution"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+ ...: additional parameters.
+
+ clip: positive real: clipping bound
+
+ stand: standardizing constant/matrix.
+
+sampleSize: integer: sample size.
+
+ Algo: "A" or "B".
+
+ cont: "left" or "right".
+
+_D_e_t_a_i_l_s:
+
+ The computation of the finite-sample under-/overshoot risk is
+ based on FFT. For more details we refer to Section 11.3 of Kohl
+ (2005).
+
+_V_a_l_u_e:
+
+ The finite-sample risk is computed.
+
+_M_e_t_h_o_d_s:
+
+ _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _D_i_s_t_r = "_N_o_r_m", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes finite-sample under-/overshoot risk in methods for
+ function 'getFixRobIC'.
+
+ _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _D_i_s_t_r = "_N_o_r_m", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes finite-sample under-/overshoot risk in methods for
+ function 'getFixRobIC'.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1968) Robust Confidence Limits. Z.
+ Wahrscheinlichkeitstheor. Verw. Geb. *10*:269-278.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+ Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite
+ Sample Risk of M-estimators on Neighborhoods.
+
+_S_e_e _A_l_s_o:
+
+ 'fiRisk-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getFixClip
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getFixClip (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getFixClip 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,65 @@
+getFixClip package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _O_p_t_i_m_a_l _C_l_i_p_p_i_n_g _B_o_u_n_d
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the optimal clipping bound
+ in case of robust models with fixed neighborhoods. This function
+ is rarely called directly. It is used to compute optimally robust
+ ICs.
+
+_U_s_a_g_e:
+
+ getFixClip(clip, Distr, risk, neighbor, ...)
+
+ ## S4 method for signature 'numeric, Norm, fiUnOvShoot,
+ ## ContNeighborhood':
+ getFixClip(clip, Distr, risk, neighbor)
+
+ ## S4 method for signature 'numeric, Norm, fiUnOvShoot,
+ ## TotalVarNeighborhood':
+ getFixClip(clip, Distr, risk, neighbor)
+
+_A_r_g_u_m_e_n_t_s:
+
+ clip: positive real: clipping bound
+
+ Distr: object of class '"Distribution"'.
+
+ risk: object of class '"RiskType"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+ ...: additional parameters.
+
+_V_a_l_u_e:
+
+ The optimal clipping bound is computed.
+
+_M_e_t_h_o_d_s:
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _D_i_s_t_r = "_N_o_r_m", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for finite-sample under-/overshoot
+ risk.
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _D_i_s_t_r = "_N_o_r_m", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for finite-sample under-/overshoot
+ risk.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1968) Robust Confidence Limits. Z.
+ Wahrscheinlichkeitstheor. Verw. Geb. *10*:269-278.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'ContIC-class', 'TotalVarIC-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getFixRobIC
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getFixRobIC (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getFixRobIC 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,70 @@
+getFixRobIC package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _O_p_t_i_m_a_l_l_y _R_o_b_u_s_t _I_C_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of optimally robust ICs in
+ case of robust models with fixed neighborhoods. This function is
+ rarely called directly.
+
+_U_s_a_g_e:
+
+ getFixRobIC(Distr, risk, neighbor, ...)
+
+ ## S4 method for signature 'Norm, fiUnOvShoot,
+ ## UncondNeighborhood':
+ getFixRobIC(Distr, risk, neighbor,
+ sampleSize, upper, maxiter, tol, warn, Algo, cont)
+
+_A_r_g_u_m_e_n_t_s:
+
+ Distr: object of class '"Distribution"'.
+
+ risk: object of class '"RiskType"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+ ...: additional parameters.
+
+sampleSize: integer: sample size.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations.
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+ Algo: "A" or "B".
+
+ cont: "left" or "right".
+
+_V_a_l_u_e:
+
+ The optimally robust IC is computed.
+
+_M_e_t_h_o_d_s:
+
+ _D_i_s_t_r = "_N_o_r_m", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the optimally robust influence curve for
+ one-dimensional normal location and finite-sample
+ under-/overshoot risk.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1968) Robust Confidence Limits. Z.
+ Wahrscheinlichkeitstheor. Verw. Geb. *10*:269-278.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'FixRobModel-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getIneffDiff
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getIneffDiff (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getIneffDiff 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,89 @@
+getIneffDiff package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _I_n_e_f_f_i_c_i_e_n_c_y _D_i_f_f_e_r_e_n_c_e_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of inefficiency differencies.
+ This function is rarely called directly. It is used to compute the
+ radius minimax IC and the least favorable radius.
+
+_U_s_a_g_e:
+
+ getIneffDiff(radius, L2Fam, neighbor, risk, biastype, ...)
+
+ ## S4 method for signature 'numeric, L2ParamFamily,
+ ## UncondNeighborhood, asMSE, BiasType':
+ getIneffDiff(
+ radius, L2Fam, neighbor, risk, biastype = symmetricBias(), loRad, upRad,
+ loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
+
+_A_r_g_u_m_e_n_t_s:
+
+ radius: neighborhood radius.
+
+ L2Fam: L2-differentiable family of probability measures.
+
+neighbor: object of class '"Neighborhood"'.
+
+ risk: object of class '"RiskType"'.
+
+biastype: object of class '"BiasType"'.
+
+ ...: additional parameters
+
+ loRad: the lower end point of the interval to be searched.
+
+ upRad: the upper end point of the interval to be searched.
+
+ loRisk: the risk at the lower end point of the interval.
+
+ upRisk: the risk at the upper end point of the interval.
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ upper.b: upper bound for the optimal clipping bound.
+
+ MaxIter: the maximum number of iterations
+
+ eps: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+_V_a_l_u_e:
+
+ The inefficieny difference between the left and the right margin
+ of a given radius interval is computed.
+
+_M_e_t_h_o_d_s:
+
+ _r_a_d_i_u_s = "_n_u_m_e_r_i_c", _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _r_i_s_k = "_a_s_M_S_E", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e":
+ computes difference of asymptotic MSE-inefficiency for the
+ boundaries of a given radius interval.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not
+ Knowing the Radius. Submitted. Appeared as discussion paper Nr.
+ 81. SFB 373 (Quantification and Simulation of Economic
+ Processes), Humboldt University, Berlin; also available under
+ <URL:
+ www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf>
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'radiusMinimaxIC', 'leastFavorableRadius'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getInfCent
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getInfCent (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getInfCent 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,110 @@
+getInfCent package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _O_p_t_i_m_a_l _C_e_n_t_e_r_i_n_g _C_o_n_s_t_a_n_t/_L_o_w_e_r _C_l_i_p_p_i_n_g _B_o_u_n_d
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the optimal centering
+ constant (contamination neighborhoods) respectively, of the
+ optimal lower clipping bound (total variation neighborhood). This
+ function is rarely called directly. It is used to compute
+ optimally robust ICs.
+
+_U_s_a_g_e:
+
+ getInfCent(L2deriv, neighbor, biastype, ...)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## TotalVarNeighborhood, BiasType':
+ getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+
+ ## S4 method for signature 'RealRandVariable,
+ ## ContNeighborhood, BiasType':
+ getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, onesidedBias':
+ getInfCent(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, asymmetricBias':
+ getInfCent(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2deriv: L2-derivative of some L2-differentiable family of
+ probability measures.
+
+neighbor: object of class '"Neighborhood"'.
+
+biastype: object of class '"BiasType"'
+
+ ...: additional parameters.
+
+ clip: optimal clipping bound.
+
+ cent: optimal centering constant.
+
+ stand: standardizing matrix.
+
+ tol.z: the desired accuracy (convergence tolerance).
+
+ symm: logical: indicating symmetry of 'L2deriv'.
+
+ trafo: matrix: transformation of the parameter.
+
+ z.comp: logical vector: indication which components of the centering
+ constant have to be computed.
+
+_V_a_l_u_e:
+
+ The optimal centering constant is computed.
+
+_M_e_t_h_o_d_s:
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computation of optimal centering constant for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computation of optimal lower clipping bound for symmetric
+ bias.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computation of optimal centering constant for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_o_n_e_s_i_d_e_d_B_i_a_s"
+ computation of optimal centering constant for onesided bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_a_s_y_m_m_e_t_r_i_c_B_i_a_s"
+ computation of optimal centering constant for asymmetric
+ bias.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'ContIC-class', 'TotalVarIC-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getInfClip
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getInfClip (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getInfClip 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,104 @@
+getInfClip package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _O_p_t_i_m_a_l _C_l_i_p_p_i_n_g _B_o_u_n_d
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the optimal clipping bound
+ in case of infinitesimal robust models. This function is rarely
+ called directly. It is used to compute optimally robust ICs.
+
+_U_s_a_g_e:
+
+ getInfClip(clip, L2deriv, risk, neighbor, ...)
+
+ ## S4 method for signature 'numeric,
+ ## UnivariateDistribution, asMSE, ContNeighborhood':
+ getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+ ## S4 method for signature 'numeric,
+ ## UnivariateDistribution, asMSE, TotalVarNeighborhood':
+ getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+ ## S4 method for signature 'numeric, EuclRandVariable,
+ ## asMSE, ContNeighborhood':
+ getInfClip(clip, L2deriv, risk, neighbor, Distr, stand, biastype, cent, trafo)
+
+ ## S4 method for signature 'numeric,
+ ## UnivariateDistribution, asUnOvShoot,
+ ## UncondNeighborhood':
+ getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+ ## S4 method for signature 'numeric,
+ ## UnivariateDistribution, asSemivar, ContNeighborhood':
+ getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+_A_r_g_u_m_e_n_t_s:
+
+ clip: positive real: clipping bound
+
+ L2deriv: L2-derivative of some L2-differentiable family of
+ probability measures.
+
+ risk: object of class '"RiskType"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+ ...: additional parameters.
+
+biastype: object of class '"BiasType"'
+
+ cent: optimal centering constant.
+
+ stand: standardizing matrix.
+
+ Distr: object of class '"Distribution"'.
+
+ symm: logical: indicating symmetry of 'L2deriv'.
+
+ trafo: matrix: transformation of the parameter.
+
+_V_a_l_u_e:
+
+ The optimal clipping bound is computed.
+
+_M_e_t_h_o_d_s:
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for asymtotic mean square error.
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for asymtotic mean square error.
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _L_2_d_e_r_i_v = "_E_u_c_l_R_a_n_d_V_a_r_i_a_b_l_e", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for asymtotic mean square error.
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for asymtotic under-/overshoot risk.
+
+ _c_l_i_p = "_n_u_m_e_r_i_c", _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_S_e_m_i_v_a_r", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ optimal clipping bound for asymtotic semivariance.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'ContIC-class', 'TotalVarIC-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getInfGamma
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getInfGamma (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getInfGamma 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,117 @@
+getInfGamma package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _O_p_t_i_m_a_l _C_l_i_p_p_i_n_g _B_o_u_n_d
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the optimal clipping
+ bound. This function is rarely called directly. It is called by
+ 'getInfClip' to compute optimally robust ICs.
+
+_U_s_a_g_e:
+
+ getInfGamma(L2deriv, risk, neighbor, biastype, ...)
+
+ ## S4 method for signature 'UnivariateDistribution, asMSE,
+ ## ContNeighborhood, BiasType':
+ getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## asGRisk, TotalVarNeighborhood, BiasType':
+ getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+ ## S4 method for signature 'RealRandVariable, asMSE,
+ ## ContNeighborhood, BiasType':
+ getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## asUnOvShoot, ContNeighborhood, BiasType':
+ getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+ ## S4 method for signature 'UnivariateDistribution, asMSE,
+ ## ContNeighborhood, onesidedBias':
+ getInfGamma(L2deriv,
+ risk, neighbor, biastype = positiveBias(), cent, clip)
+
+ ## S4 method for signature 'UnivariateDistribution, asMSE,
+ ## ContNeighborhood, asymmetricBias':
+ getInfGamma(L2deriv,
+ risk, neighbor, biastype = asymmetricBias(), cent, clip)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2deriv: L2-derivative of some L2-differentiable family of
+ probability measures.
+
+ risk: object of class '"RiskType"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+biastype: object of class '"BiasType"'
+
+ ...: additional parameters
+
+ cent: optimal centering constant.
+
+ clip: optimal clipping bound.
+
+ stand: standardizing matrix.
+
+ Distr: object of class '"Distribution"'.
+
+_D_e_t_a_i_l_s:
+
+ The function is used in case of asymptotic G-risks; confer
+ Ruckdeschel and Rieder (2004).
+
+_M_e_t_h_o_d_s:
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ used by 'getInfClip' for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_G_R_i_s_k", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ used by 'getInfClip' for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ used by 'getInfClip' for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ used by 'getInfClip' for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_o_n_e_s_i_d_e_d_B_i_a_s"
+ used by 'getInfClip' for onesided bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_a_s_y_m_m_e_t_r_i_c_B_i_a_s"
+ used by 'getInfClip' for asymmetric bias.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+ General Loss Functions. Statistics & Decisions _22_, 201-223.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'asGRisk-class', 'asMSE-class', 'asUnOvShoot-class',
+ 'ContIC-class', 'TotalVarIC-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getInfRobIC
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getInfRobIC (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getInfRobIC 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,185 @@
+getInfRobIC package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _O_p_t_i_m_a_l_l_y _R_o_b_u_s_t _I_C_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of optimally robust ICs in
+ case of infinitesimal robust models. This function is rarely
+ called directly.
+
+_U_s_a_g_e:
+
+ getInfRobIC(L2deriv, risk, neighbor, ...)
+
+ ## S4 method for signature 'UnivariateDistribution, asCov,
+ ## ContNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution, asCov,
+ ## TotalVarNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
+
+ ## S4 method for signature 'RealRandVariable, asCov,
+ ## ContNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution, asBias,
+ ## UncondNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'RealRandVariable, asBias,
+ ## ContNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## asHampel, UncondNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'RealRandVariable, asHampel,
+ ## ContNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## asGRisk, UncondNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'RealRandVariable, asGRisk,
+ ## ContNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## asUnOvShoot, UncondNeighborhood':
+ getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2deriv: L2-derivative of some L2-differentiable family of
+ probability measures.
+
+ risk: object of class '"RiskType"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+ ...: additional parameters.
+
+biastype: object of class '"BiasType"'.
+
+ Distr: object of class '"Distribution"'.
+
+ symm: logical: indicating symmetry of 'L2deriv'.
+
+DistrSymm: object of class '"DistributionSymmetry"'.
+
+L2derivSymm: object of class '"FunSymmList"'.
+
+L2derivDistrSymm: object of class '"DistrSymmList"'.
+
+ Finfo: Fisher information matrix.
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ trafo: matrix: transformation of the parameter.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations.
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+_V_a_l_u_e:
+
+ The optimally robust IC is computed.
+
+_M_e_t_h_o_d_s:
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_C_o_v", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the classical optimal influence curve for L2
+ differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_C_o_v", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the classical optimal influence curve for L2
+ differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _r_i_s_k = "_a_s_C_o_v", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the classical optimal influence curve for L2
+ differentiable parametric families with unknown
+ k-dimensional parameter (k > 1) where the underlying
+ distribution is univariate.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the bias optimal influence curve for L2
+ differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the bias optimal influence curve for L2
+ differentiable parametric families with unknown
+ k-dimensional parameter (k > 1) where the underlying
+ distribution is univariate.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_H_a_m_p_e_l", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the optimally robust influence curve for L2
+ differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _r_i_s_k = "_a_s_H_a_m_p_e_l", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the optimally robust influence curve for L2
+ differentiable parametric families with unknown
+ k-dimensional parameter (k > 1) where the underlying
+ distribution is univariate.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_G_R_i_s_k", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the optimally robust influence curve for L2
+ differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _r_i_s_k = "_a_s_G_R_i_s_k", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the optimally robust influence curve for L2
+ differentiable parametric families with unknown
+ k-dimensional parameter (k > 1) where the underlying
+ distribution is univariate.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _r_i_s_k = "_a_s_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d"
+ computes the optimally robust influence curve for
+ one-dimensional L2 differentiable parametric families and
+ asymptotic under-/overshoot risk.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+ General Loss Functions. Statistics & Decisions *22*: 201-223.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'InfRobModel-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getInfStand
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getInfStand (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getInfStand 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,105 @@
+getInfStand package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _S_t_a_n_d_a_r_d_i_z_i_n_g _M_a_t_r_i_x
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the standardizing matrix
+ which takes care of the Fisher consistency of the corresponding
+ IC. This function is rarely called directly. It is used to
+ compute optimally robust ICs.
+
+_U_s_a_g_e:
+
+ getInfStand(L2deriv, neighbor, biastype, ...)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## TotalVarNeighborhood, BiasType':
+ getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+
+ ## S4 method for signature 'RealRandVariable,
+ ## ContNeighborhood, BiasType':
+ getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ getInfStand(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, trafo)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ getInfStand(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, trafo)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2deriv: L2-derivative of some L2-differentiable family of
+ probability measures.
+
+neighbor: object of class '"Neighborhood"'
+
+biastype: object of class '"BiasType"'
+
+ ...: additional parameters
+
+ clip: optimal clipping bound.
+
+ cent: optimal centering constant.
+
+ stand: standardizing matrix.
+
+ Distr: object of class '"Distribution"'.
+
+ trafo: matrix: transformation of the parameter.
+
+ A.comp: matrix: indication which components of the standardizing
+ matrix have to be computed.
+
+_V_a_l_u_e:
+
+ The standardizing matrix is computed.
+
+_M_e_t_h_o_d_s:
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computes standardizing matrix for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computes standardizing matrix for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computes standardizing matrix for symmetric bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_o_n_e_s_i_d_e_d_B_i_a_s"
+ computes standardizing matrix for onesided bias.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_a_s_y_m_m_e_t_r_i_c_B_i_a_s"
+ computes standardizing matrix for asymmetric bias.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'ContIC-class', 'TotalVarIC-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getL1normL2deriv
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getL1normL2deriv (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getL1normL2deriv 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,44 @@
+getL1normL2deriv package:ROptEst R Documentation
+
+_C_a_l_c_u_l_a_t_i_o_n _o_f _L_1 _n_o_r_m _o_f _L_2_d_e_r_i_v_a_t_i_v_e
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Methods to calculate the L1 norm of the L2derivative in a smooth
+ parametric model.
+
+_U_s_a_g_e:
+
+ getL1normL2deriv(L2deriv, ...)
+ ## S4 method for signature 'UnivariateDistribution':
+ getL1normL2deriv(L2deriv,
+ cent, ...)
+
+ ## S4 method for signature 'UnivariateDistribution':
+ getL1normL2deriv(L2deriv,
+ cent, stand, Distr, ...)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2deriv: L2derivative of the model
+
+ cent: centering Lagrange Multiplier
+
+ stand: standardizing Lagrange Multiplier
+
+ Distr: distribution of the L2derivative
+
+ ...: further arguments (not used at the moment)
+
+_V_a_l_u_e:
+
+ L1 norm of the L2derivative
+
+_A_u_t_h_o_r(_s):
+
+ Peter Ruckdeschel Peter.Ruckdeschel at uni-bayreuth.de
+
+_E_x_a_m_p_l_e_s:
+
+ ##
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getL2normL2deriv
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getL2normL2deriv (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getL2normL2deriv 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,33 @@
+getL2normL2deriv package:ROptEst R Documentation
+
+_C_a_l_c_u_l_a_t_i_o_n _o_f _L_2 _n_o_r_m _o_f _L_2_d_e_r_i_v_a_t_i_v_e
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Function to calculate the L2 norm of the L2derivative in a smooth
+ parametric model.
+
+_U_s_a_g_e:
+
+ getL2normL2deriv(aFinfo, cent, ...)
+
+_A_r_g_u_m_e_n_t_s:
+
+ aFinfo: trace of the Fisher information
+
+ cent: centering
+
+ ...: further arguments (not used at the moment)
+
+_V_a_l_u_e:
+
+ L2 norm of the L2derivative
+
+_A_u_t_h_o_r(_s):
+
+ Peter Ruckdeschel Peter.Ruckdeschel at uni-bayreuth.de
+
+_E_x_a_m_p_l_e_s:
+
+ ##
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/getRiskIC
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/getRiskIC (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/getRiskIC 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,159 @@
+getRiskIC package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _a _r_i_s_k _f_o_r _a_n _I_C
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of a risk for an IC.
+
+_U_s_a_g_e:
+
+ getRiskIC(IC, risk, neighbor, L2Fam, ...)
+
+ ## S4 method for signature 'IC, asCov, missing, missing':
+ getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, asCov, missing,
+ ## L2ParamFamily':
+ getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, trAsCov, missing, missing':
+ getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, trAsCov, missing,
+ ## L2ParamFamily':
+ getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, asBias, UncondNeighborhood,
+ ## missing':
+ getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, asBias, UncondNeighborhood,
+ ## L2ParamFamily':
+ getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+ ## missing':
+ getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+ ## L2ParamFamily':
+ getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+ ## S4 method for signature 'TotalVarIC, asUnOvShoot,
+ ## UncondNeighborhood, missing':
+ getRiskIC(IC, risk, neighbor)
+
+ ## S4 method for signature 'IC, fiUnOvShoot,
+ ## ContNeighborhood, missing':
+ getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+
+ ## S4 method for signature 'IC, fiUnOvShoot,
+ ## TotalVarNeighborhood, missing':
+ getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+
+_A_r_g_u_m_e_n_t_s:
+
+ IC: object of class '"InfluenceCurve"'
+
+ risk: object of class '"RiskType"'.
+
+neighbor: object of class '"Neighborhood"'.
+
+ L2Fam: object of class '"L2ParamFamily"'.
+
+ ...: additional parameters
+
+biastype: object of class '"BiasType"'.
+
+ tol: the desired accuracy (convergence tolerance).
+
+sampleSize: integer: sample size.
+
+ Algo: "A" or "B".
+
+ cont: "left" or "right".
+
+_D_e_t_a_i_l_s:
+
+ To make sure that the results are valid, it is recommended to
+ include an additional check of the IC properties of 'IC' using
+ 'checkIC'.
+
+_V_a_l_u_e:
+
+ The risk of an IC is computed.
+
+_M_e_t_h_o_d_s:
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_C_o_v", _n_e_i_g_h_b_o_r = "_m_i_s_s_i_n_g", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ asymptotic covariance of 'IC'.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_C_o_v", _n_e_i_g_h_b_o_r = "_m_i_s_s_i_n_g", _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y"
+ asymptotic covariance of 'IC' under 'L2Fam'.
+
+ _I_C = "_I_C", _r_i_s_k = "_t_r_A_s_C_o_v", _n_e_i_g_h_b_o_r = "_m_i_s_s_i_n_g", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ asymptotic covariance of 'IC'.
+
+ _I_C = "_I_C", _r_i_s_k = "_t_r_A_s_C_o_v", _n_e_i_g_h_b_o_r = "_m_i_s_s_i_n_g", _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y"
+ asymptotic covariance of 'IC' under 'L2Fam'.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ asymptotic bias of 'IC' under convex contaminations.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y"
+ asymptotic bias of 'IC' under convex contaminations and
+ 'L2Fam'.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ asymptotic bias of 'IC' in case of total variation
+ neighborhoods.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_B_i_a_s", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y"
+ asymptotic bias of 'IC' under 'L2Fam' in case of total
+ variation neighborhoods.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ asymptotic mean square error of 'IC'.
+
+ _I_C = "_I_C", _r_i_s_k = "_a_s_M_S_E", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y"
+ asymptotic mean square error of 'IC' under 'L2Fam'.
+
+ _I_C = "_T_o_t_a_l_V_a_r_I_C", _r_i_s_k = "_a_s_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ asymptotic under-/overshoot risk of 'IC'.
+
+ _I_C = "_I_C", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ finite-sample under-/overshoot risk of 'IC'.
+
+ _I_C = "_I_C", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _L_2_F_a_m = "_m_i_s_s_i_n_g"
+ finite-sample under-/overshoot risk of 'IC'.
+
+_N_o_t_e:
+
+ This generic function is still under construction.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1968) Robust Confidence Limits. Z.
+ Wahrscheinlichkeitstheor. Verw. Geb. *10*:269-278.
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+ Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite
+ Sample Risk of M-estimators on Neighborhoods.
+
+_S_e_e _A_l_s_o:
+
+ 'getRiskIC-methods', 'InfRobModel-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/leastFavorableRadius
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/leastFavorableRadius (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/leastFavorableRadius 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,92 @@
+leastFavorableRadius package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _L_e_a_s_t _F_a_v_o_r_a_b_l_e _R_a_d_i_i
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of least favorable radii.
+
+_U_s_a_g_e:
+
+ leastFavorableRadius(L2Fam, neighbor, risk, ...)
+
+ ## S4 method for signature 'L2ParamFamily,
+ ## UncondNeighborhood, asGRisk':
+ leastFavorableRadius(
+ L2Fam, neighbor, risk, biastype = symmetricBias(), rho, upRad = 1,
+ z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
+ tol = .Machine$double.eps^0.4, warn = FALSE)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2Fam: L2-differentiable family of probability measures.
+
+neighbor: object of class '"Neighborhood"'.
+
+ risk: object of class '"RiskType"'.
+
+ ...: additional parameters
+
+biastype: object of class '"BiasType"'.
+
+ upRad: the upper end point of the radius interval to be searched.
+
+ rho: The considered radius interval is: [r*rho, r/rho] with 0 <
+ rho < 1.
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+_V_a_l_u_e:
+
+ The least favorable radius and the corresponding inefficiency are
+ computed.
+
+_M_e_t_h_o_d_s:
+
+ _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _r_i_s_k = "_a_s_G_R_i_s_k"
+ computation of the least favorable radius.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not
+ Knowing the Radius. Statistical Methods and Applications _17_(1)
+ 13-40.
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not
+ Knowing the Radius. Submitted. Appeared as discussion paper Nr.
+ 81. SFB 373 (Quantification and Simulation of Economic
+ Processes), Humboldt University, Berlin; also available under
+ <URL:
+ www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf>
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'radiusMinimaxIC'
+
+_E_x_a_m_p_l_e_s:
+
+ N <- NormLocationFamily(mean=0, sd=1)
+ leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5)
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/locMEstimator
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/locMEstimator (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/locMEstimator 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,54 @@
+locMEstimator package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _l_o_c_a_t_i_o_n _M _e_s_t_i_m_a_t_o_r_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of location M estimators.
+
+_U_s_a_g_e:
+
+ locMEstimator(x, IC, ...)
+
+ ## S4 method for signature 'numeric, InfluenceCurve':
+ locMEstimator(x, IC, eps = .Machine$double.eps^0.5)
+
+_A_r_g_u_m_e_n_t_s:
+
+ x: sample
+
+ IC: object of class '"InfluenceCurve"'
+
+ ...: additional parameters
+
+ eps: the desired accuracy (convergence tolerance).
+
+_V_a_l_u_e:
+
+ Returns a list with component
+
+ loc: M estimator of location
+
+_M_e_t_h_o_d_s:
+
+ _x = "_n_u_m_e_r_i_c", _I_C = "_I_n_f_l_u_e_n_c_e_C_u_r_v_e" univariate location.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1964) Robust estimation of a location parameter.
+ Ann. Math. Stat. *35*: 73-101.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'InfluenceCurve-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/lowerCaseRadius
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/lowerCaseRadius (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/lowerCaseRadius 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,62 @@
+lowerCaseRadius package:ROptEst R Documentation
+
+_C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _l_o_w_e_r _c_a_s_e _r_a_d_i_u_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ The lower case radius is computed; confer Subsection 2.1.2 in
+ Kohl (2005) and formula (4.5) in Ruckdeschel (2005).
+
+_U_s_a_g_e:
+
+ lowerCaseRadius(L2Fam, neighbor, risk, biastype, ...)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2Fam: L2 differentiable parametric family
+
+neighbor: object of class '"Neighborhood"'
+
+ risk: object of class '"RiskType"'
+
+biastype: object of class '"BiasType"'
+
+ ...: additional parameters
+
+_V_a_l_u_e:
+
+ lower case radius
+
+_M_e_t_h_o_d_s:
+
+ _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _r_i_s_k = "_a_s_M_S_E", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ lower case radius for risk '"asMSE"' in case of
+ '"ContNeighborhood"' for symmetric bias.
+
+ _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _r_i_s_k = "_a_s_M_S_E", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ lower case radius for risk '"asMSE"' in case of
+ '"TotalVarNeighborhood"'; (argument biastype is just for
+ signature reasons).
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+_S_e_e _A_l_s_o:
+
+ 'L2ParamFamily-class', 'Neighborhood-class'
+
+_E_x_a_m_p_l_e_s:
+
+ lowerCaseRadius(BinomFamily(size = 10), ContNeighborhood(), asMSE())
+ lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/minmaxBias
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/minmaxBias (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/minmaxBias 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,121 @@
+minmaxBias package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _B_i_a_s-_O_p_t_i_m_a_l_l_y _R_o_b_u_s_t _I_C_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of bias-optimally robust ICs
+ in case of infinitesimal robust models. This function is rarely
+ called directly.
+
+_U_s_a_g_e:
+
+ minmaxBias(L2deriv, neighbor, biastype, ...)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, BiasType':
+ minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## ContNeighborhood, asymmetricBias':
+ minmaxBias(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'UnivariateDistribution,
+ ## TotalVarNeighborhood, BiasType':
+ minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+ ## S4 method for signature 'RealRandVariable,
+ ## ContNeighborhood, BiasType':
+ minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2deriv: L2-derivative of some L2-differentiable family of
+ probability measures.
+
+neighbor: object of class '"Neighborhood"'.
+
+biastype: object of class '"BiasType"'.
+
+ ...: additional parameters.
+
+ Distr: object of class '"Distribution"'.
+
+ symm: logical: indicating symmetry of 'L2deriv'.
+
+DistrSymm: object of class '"DistributionSymmetry"'.
+
+L2derivSymm: object of class '"FunSymmList"'.
+
+L2derivDistrSymm: object of class '"DistrSymmList"'.
+
+ Finfo: Fisher information matrix.
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ trafo: matrix: transformation of the parameter.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations.
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+_V_a_l_u_e:
+
+ The bias-optimally robust IC is computed.
+
+_M_e_t_h_o_d_s:
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computes the bias optimal influence curve for symmetric bias
+ for L2 differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_a_s_y_m_m_e_t_r_i_c_B_i_a_s"
+ computes the bias optimal influence curve for asymmetric bias
+ for L2 differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_U_n_i_v_a_r_i_a_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _n_e_i_g_h_b_o_r = "_T_o_t_a_l_V_a_r_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computes the bias optimal influence curve for symmetric bias
+ for L2 differentiable parametric families with unknown
+ one-dimensional parameter.
+
+ _L_2_d_e_r_i_v = "_R_e_a_l_R_a_n_d_V_a_r_i_a_b_l_e", _n_e_i_g_h_b_o_r = "_C_o_n_t_N_e_i_g_h_b_o_r_h_o_o_d", _b_i_a_s_t_y_p_e = "_B_i_a_s_T_y_p_e"
+ computes the bias optimal influence curve for symmetric bias
+ for L2 differentiable parametric families with unknown
+ k-dimensional parameter (k > 1) where the underlying
+ distribution is univariate.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence
+ Curves. Mathematical Methods in Statistics _14_(1), 105-131.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'InfRobModel-class'
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/optIC
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/optIC (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/optIC 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,117 @@
+optIC package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _o_p_t_i_m_a_l_l_y _r_o_b_u_s_t _I_C_s
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of optimally robust ICs.
+
+_U_s_a_g_e:
+
+ optIC(model, risk, ...)
+
+ ## S4 method for signature 'L2ParamFamily, asCov':
+ optIC(model, risk)
+
+ ## S4 method for signature 'InfRobModel, asRisk':
+ optIC(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
+ ## S4 method for signature 'InfRobModel, asUnOvShoot':
+ optIC(model, risk, biastype = symmetricBias(),
+ upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE)
+
+ ## S4 method for signature 'FixRobModel, fiUnOvShoot':
+ optIC(model, risk, sampleSize, upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
+
+_A_r_g_u_m_e_n_t_s:
+
+ model: probability model.
+
+ risk: object of class '"RiskType"'.
+
+ ...: additional parameters.
+
+biastype: object of class '"BiasType"'
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations.
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+sampleSize: integer: sample size.
+
+ Algo: "A" or "B".
+
+ cont: "left" or "right".
+
+_D_e_t_a_i_l_s:
+
+ In case of the finite-sample risk '"fiUnOvShoot"' one can choose
+ between two algorithms for the computation of this risk where the
+ least favorable contamination is assumed to be left or right of
+ some bound. For more details we refer to Section 11.3 of Kohl
+ (2005).
+
+_V_a_l_u_e:
+
+ Some optimally robust IC is computed.
+
+_M_e_t_h_o_d_s:
+
+ _m_o_d_e_l = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _r_i_s_k = "_a_s_C_o_v" computes classical optimal
+ influence curve for L2 differentiable parametric families.
+
+ _m_o_d_e_l = "_I_n_f_R_o_b_M_o_d_e_l", _r_i_s_k = "_a_s_R_i_s_k" computes optimally robust
+ influence curve for robust models with infinitesimal
+ neighborhoods and various asymptotic risks.
+
+ _m_o_d_e_l = "_I_n_f_R_o_b_M_o_d_e_l", _r_i_s_k = "_a_s_U_n_O_v_S_h_o_o_t" computes optimally
+ robust influence curve for robust models with infinitesimal
+ neighborhoods and asymptotic under-/overshoot risk.
+
+ _m_o_d_e_l = "_F_i_x_R_o_b_M_o_d_e_l", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t" computes optimally
+ robust influence curve for robust models with fixed
+ neighborhoods and finite-sample under-/overshoot risk.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1968) Robust Confidence Limits. Z.
+ Wahrscheinlichkeitstheor. Verw. Geb. *10*:269-278.
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'InfluenceCurve-class', 'RiskType-class'
+
+_E_x_a_m_p_l_e_s:
+
+ B <- BinomFamily(size = 25, prob = 0.25)
+
+ ## classical optimal IC
+ IC0 <- optIC(model = B, risk = asCov())
+ plot(IC0) # plot IC
+ checkIC(IC0, B)
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/optRisk
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/optRisk (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/optRisk 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,103 @@
+optRisk package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _m_i_n_i_m_a_l _r_i_s_k
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the optimal (i.e.,
+ minimal) risk for a probability model.
+
+_U_s_a_g_e:
+
+ optRisk(model, risk, ...)
+
+ ## S4 method for signature 'L2ParamFamily, asCov':
+ optRisk(model, risk)
+
+ ## S4 method for signature 'InfRobModel, asRisk':
+ optRisk(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
+ ## S4 method for signature 'FixRobModel, fiUnOvShoot':
+ optRisk(model, risk, sampleSize, upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
+
+_A_r_g_u_m_e_n_t_s:
+
+ model: probability model
+
+ risk: object of class 'RiskType'
+
+ ...: additional parameters
+
+biastype: object of class 'BiasType'
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+sampleSize: integer: sample size.
+
+ Algo: "A" or "B".
+
+ cont: "left" or "right".
+
+_D_e_t_a_i_l_s:
+
+ In case of the finite-sample risk '"fiUnOvShoot"' one can choose
+ between two algorithms for the computation of this risk where the
+ least favorable contamination is assumed to be left or right of
+ some bound. For more details we refer to Section 11.3 of Kohl
+ (2005).
+
+_V_a_l_u_e:
+
+ The minimal risk is computed.
+
+_M_e_t_h_o_d_s:
+
+ _m_o_d_e_l = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _r_i_s_k = "_a_s_C_o_v" asymptotic covariance of
+ L2 differentiable parameteric family.
+
+ _m_o_d_e_l = "_I_n_f_R_o_b_M_o_d_e_l", _r_i_s_k = "_a_s_R_i_s_k" asymptotic risk of a
+ infinitesimal robust model.
+
+ _m_o_d_e_l = "_F_i_x_R_o_b_M_o_d_e_l", _r_i_s_k = "_f_i_U_n_O_v_S_h_o_o_t" finite-sample
+ under-/overshoot risk of a robust model with fixed
+ neighborhood.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Huber, P.J. (1968) Robust Confidence Limits. Z.
+ Wahrscheinlichkeitstheor. Verw. Geb. *10*:269-278.
+
+ Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats.
+ *8*: 106-115.
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'RiskType-class'
+
+_E_x_a_m_p_l_e_s:
+
+ optRisk(model = NormLocationScaleFamily(), risk = asCov())
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/radiusMinimaxIC
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/radiusMinimaxIC (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/radiusMinimaxIC 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,84 @@
+radiusMinimaxIC package:ROptEst R Documentation
+
+_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _r_a_d_i_u_s _m_i_n_i_m_a_x _I_C
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Generic function for the computation of the radius minimax IC.
+
+_U_s_a_g_e:
+
+ radiusMinimaxIC(L2Fam, neighbor, risk, ...)
+
+ ## S4 method for signature 'L2ParamFamily,
+ ## UncondNeighborhood, asGRisk':
+ radiusMinimaxIC(
+ L2Fam, neighbor, risk, biastype = symmetricBias(),
+ loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
+ maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
+
+_A_r_g_u_m_e_n_t_s:
+
+ L2Fam: L2-differentiable family of probability measures.
+
+neighbor: object of class '"Neighborhood"'.
+
+ risk: object of class '"RiskType"'.
+
+ ...: additional parameters.
+
+biastype: object of class '"BiasType"'.
+
+ loRad: the lower end point of the interval to be searched.
+
+ upRad: the upper end point of the interval to be searched.
+
+ z.start: initial value for the centering constant.
+
+ A.start: initial value for the standardizing matrix.
+
+ upper: upper bound for the optimal clipping bound.
+
+ maxiter: the maximum number of iterations
+
+ tol: the desired accuracy (convergence tolerance).
+
+ warn: logical: print warnings.
+
+_V_a_l_u_e:
+
+ The radius minimax IC is computed.
+
+_M_e_t_h_o_d_s:
+
+ _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _r_i_s_k = "_a_s_G_R_i_s_k":
+ computation of the radius minimax IC for an L2 differentiable
+ parametric family.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de, Peter Ruckdeschel
+ Peter.Ruckdeschel at uni-bayreuth.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not
+ Knowing the Radius. Submitted. Appeared as discussion paper Nr.
+ 81. SFB 373 (Quantification and Simulation of Economic
+ Processes), Humboldt University, Berlin; also available under
+ <URL:
+ www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf>
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'radiusMinimaxIC'
+
+_E_x_a_m_p_l_e_s:
+
+ N <- NormLocationFamily(mean=0, sd=1)
+ radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5)
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/trAsCov-class
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/trAsCov-class (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/trAsCov-class 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,44 @@
+trAsCov-class package:ROptEst R Documentation
+
+_T_r_a_c_e _o_f _a_s_y_m_p_t_o_t_i_c _c_o_v_a_r_i_a_n_c_e
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Class of trace of asymptotic covariance.
+
+_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:
+
+ Objects can be created by calls of the form 'new("trAsCov", ...)'.
+ More frequently they are created via the generating function
+ 'trAsCov'.
+
+_S_l_o_t_s:
+
+ '_t_y_p_e': Object of class '"character"': “trace of asymptotic
+ covariance”.
+
+_E_x_t_e_n_d_s:
+
+ Class '"asRisk"', directly.
+ Class '"RiskType"', by class '"asRisk"'.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Rieder, H. (1994) _Robust Asymptotic Statistics_. New York:
+ Springer.
+
+ Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
+ of Robustness_. Bayreuth: Dissertation.
+
+_S_e_e _A_l_s_o:
+
+ 'asRisk-class', 'trAsCov'
+
+_E_x_a_m_p_l_e_s:
+
+ new("trAsCov")
+
Added: pkg/ROptEst.Rcheck/ROptEst/help/trFiCov-class
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/help/trFiCov-class (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/help/trFiCov-class 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,41 @@
+trFiCov-class package:ROptEst R Documentation
+
+_T_r_a_c_e _o_f _f_i_n_i_t_e-_s_a_m_p_l_e _c_o_v_a_r_i_a_n_c_e
+
+_D_e_s_c_r_i_p_t_i_o_n:
+
+ Class of trace of finite-sample covariance.
+
+_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:
+
+ Objects can be created by calls of the form 'new("trFiCov", ...)'.
+ More frequently they are created via the generating function
+ 'trFiCov'.
+
+_S_l_o_t_s:
+
+ '_t_y_p_e': Object of class '"character"': “trace of finite-sample
+ covariance”.
+
+_E_x_t_e_n_d_s:
+
+ Class '"fiRisk"', directly.
+ Class '"RiskType"', by class '"fiRisk"'.
+
+_A_u_t_h_o_r(_s):
+
+ Matthias Kohl Matthias.Kohl at stamats.de
+
+_R_e_f_e_r_e_n_c_e_s:
+
+ Ruckdeschel, P. and Kohl, M. (2005) How to approximate the finite
+ sample risk of M-estimators.
+
+_S_e_e _A_l_s_o:
+
+ 'fiRisk-class', 'trFiCov'
+
+_E_x_a_m_p_l_e_s:
+
+ new("trFiCov")
+
Added: pkg/ROptEst.Rcheck/ROptEst/html/00Index.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/00Index.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/00Index.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,311 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Optimally robust estimation</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+<h1>Optimally robust estimation <img class="toplogo" src="../../../doc/html/logo.jpg" alt="[R logo]"></h1>
+
+<hr>
+
+<div align="center">
+<a href="../../../doc/html/packages.html"><img src="../../../doc/html/left.jpg"
+alt="[Package List]" width="30" height="30" border="0"></a>
+<a href="../../../doc/html/index.html"><img src="../../../doc/html/up.jpg"
+alt="[Top]" width="30" height="30" border="0"></a>
+</div>
+
+<h2>Documentation for package ‘ROptEst’ version 0.6.0</h2>
+
+<h2>Help Pages</h2>
+
+<p align="center">
+<a href="#G">G</a>
+<a href="#L">L</a>
+<a href="#M">M</a>
+<a href="#O">O</a>
+<a href="#R">R</a>
+<a href="#T">T</a>
+</p>
+<table width="100%">
+</table>
+
+<h2><a name="G">-- G --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getAsRisk.html">getAsRisk-methods</a></td>
+<td>Generic Function for Computation of Asymptotic Risks</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,ContNeighborhood,missing,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getBiasIC.html">getBiasIC-methods</a></td>
+<td>Generic function for the computation of the asymptotic bias for an IC</td></tr>
+<tr><td width="25%"><a href="getFiRisk.html">getFiRisk</a></td>
+<td>Generic Function for Computation of Finite-Sample Risks</td></tr>
+<tr><td width="25%"><a href="getFiRisk.html">getFiRisk,fiUnOvShoot,Norm,ContNeighborhood-method</a></td>
+<td>Generic Function for Computation of Finite-Sample Risks</td></tr>
+<tr><td width="25%"><a href="getFiRisk.html">getFiRisk,fiUnOvShoot,Norm,TotalVarNeighborhood-method</a></td>
+<td>Generic Function for Computation of Finite-Sample Risks</td></tr>
+<tr><td width="25%"><a href="getFiRisk.html">getFiRisk-methods</a></td>
+<td>Generic Function for Computation of Finite-Sample Risks</td></tr>
+<tr><td width="25%"><a href="getFixClip.html">getFixClip</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getFixClip.html">getFixClip,numeric,Norm,fiUnOvShoot,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getFixClip.html">getFixClip,numeric,Norm,fiUnOvShoot,TotalVarNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getFixClip.html">getFixClip-methods</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getFixRobIC.html">getFixRobIC</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getFixRobIC.html">getFixRobIC,Norm,fiUnOvShoot,UncondNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getFixRobIC.html">getFixRobIC-methods</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff</a></td>
+<td>Generic Function for the Computation of Inefficiency Differences</td></tr>
+<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method</a></td>
+<td>Generic Function for the Computation of Inefficiency Differences</td></tr>
+<tr><td width="25%"><a href="getIneffDiff.html">getIneffDiff-methods</a></td>
+<td>Generic Function for the Computation of Inefficiency Differences</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfCent.html">getInfCent-methods</a></td>
+<td>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asMSE,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfClip.html">getInfClip-methods</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfGamma.html">getInfGamma-methods</a></td>
+<td>Generic Function for the Computation of the Optimal Clipping Bound</td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfRobIC.html">getInfRobIC-methods</a></td>
+<td>Generic Function for the Computation of Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getInfStand.html">getInfStand-methods</a></td>
+<td>Generic Function for the Computation of the Standardizing Matrix </td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv,RealRandVariable-method</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv,UnivariateDistribution-method</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL1normL2deriv.html">getL1normL2deriv-methods</a></td>
+<td>Calculation of L1 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getL2normL2deriv.html">getL2normL2deriv</a></td>
+<td>Calculation of L2 norm of L2derivative</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asBias,UncondNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asCov,missing,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,asMSE,UncondNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,trAsCov,missing,L2ParamFamily-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,IC,trAsCov,missing,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+<tr><td width="25%"><a href="getRiskIC.html">getRiskIC-methods</a></td>
+<td>Generic function for the computation of a risk for an IC</td></tr>
+</table>
+
+<h2><a name="L">-- L --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius</a></td>
+<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
+<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method</a></td>
+<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
+<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius-methods</a></td>
+<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
+<tr><td width="25%"><a href="locMEstimator.html">locMEstimator</a></td>
+<td>Generic function for the computation of location M estimators</td></tr>
+<tr><td width="25%"><a href="locMEstimator.html">locMEstimator,numeric,InfluenceCurve-method</a></td>
+<td>Generic function for the computation of location M estimators</td></tr>
+<tr><td width="25%"><a href="locMEstimator.html">locMEstimator-methods</a></td>
+<td>Generic function for the computation of location M estimators</td></tr>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius</a></td>
+<td>Computation of the lower case radius</td></tr>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method</a></td>
+<td>Computation of the lower case radius</td></tr>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method</a></td>
+<td>Computation of the lower case radius</td></tr>
+<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius-methods</a></td>
+<td>Computation of the lower case radius</td></tr>
+</table>
+
+<h2><a name="M">-- M --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+<tr><td width="25%"><a href="minmaxBias.html">minmaxBias-methods</a></td>
+<td>Generic Function for the Computation of Bias-Optimally Robust ICs </td></tr>
+</table>
+
+<h2><a name="O">-- O --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="optIC.html">optIC</a></td>
+<td>Generic function for the computation of optimally robust ICs</td></tr>
+<tr><td width="25%"><a href="optIC.html">optIC,FixRobModel,fiUnOvShoot-method</a></td>
+<td>Generic function for the computation of optimally robust ICs</td></tr>
+<tr><td width="25%"><a href="optIC.html">optIC,InfRobModel,asRisk-method</a></td>
+<td>Generic function for the computation of optimally robust ICs</td></tr>
+<tr><td width="25%"><a href="optIC.html">optIC,InfRobModel,asUnOvShoot-method</a></td>
+<td>Generic function for the computation of optimally robust ICs</td></tr>
+<tr><td width="25%"><a href="optIC.html">optIC,L2ParamFamily,asCov-method</a></td>
+<td>Generic function for the computation of optimally robust ICs</td></tr>
+<tr><td width="25%"><a href="optIC.html">optIC-methods</a></td>
+<td>Generic function for the computation of optimally robust ICs</td></tr>
+<tr><td width="25%"><a href="optRisk.html">optRisk</a></td>
+<td>Generic function for the computation of the minimal risk</td></tr>
+<tr><td width="25%"><a href="optRisk.html">optRisk,FixRobModel,fiUnOvShoot-method</a></td>
+<td>Generic function for the computation of the minimal risk</td></tr>
+<tr><td width="25%"><a href="optRisk.html">optRisk,InfRobModel,asRisk-method</a></td>
+<td>Generic function for the computation of the minimal risk</td></tr>
+<tr><td width="25%"><a href="optRisk.html">optRisk,L2ParamFamily,asCov-method</a></td>
+<td>Generic function for the computation of the minimal risk</td></tr>
+<tr><td width="25%"><a href="optRisk.html">optRisk-methods</a></td>
+<td>Generic function for the computation of the minimal risk</td></tr>
+</table>
+
+<h2><a name="R">-- R --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC</a></td>
+<td>Generic function for the computation of the radius minimax IC</td></tr>
+<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method</a></td>
+<td>Generic function for the computation of the radius minimax IC</td></tr>
+<tr><td width="25%"><a href="radiusMinimaxIC.html">radiusMinimaxIC-methods</a></td>
+<td>Generic function for the computation of the radius minimax IC</td></tr>
+</table>
+
+<h2><a name="T">-- T --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="trAsCov-class.html">trAsCov-class</a></td>
+<td>Trace of asymptotic covariance</td></tr>
+<tr><td width="25%"><a href="trFiCov-class.html">trFiCov-class</a></td>
+<td>Trace of finite-sample covariance</td></tr>
+</table>
+</body></html>
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===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getAsRisk.html (rev 0)
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+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for Computation of Asymptotic Risks</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getAsRisk {ROptEst}"><tr><td>getAsRisk {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for Computation of Asymptotic Risks</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of asymptotic risks.
+This function is rarely called directly. It is used by
+other functions.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getAsRisk(risk, L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'asMSE, UnivariateDistribution,
+## Neighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asMSE, EuclRandVariable,
+## Neighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asBias, UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
+
+## S4 method for signature 'asBias, UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
+
+## S4 method for signature 'asBias, RealRandVariable,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
+ z.start, A.start, maxiter, tol)
+
+## S4 method for signature 'asCov, UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+## S4 method for signature 'asCov, UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+## S4 method for signature 'asCov, RealRandVariable,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+
+## S4 method for signature 'trAsCov,
+## UnivariateDistribution, UncondNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+## S4 method for signature 'trAsCov, RealRandVariable,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+
+## S4 method for signature 'asUnOvShoot,
+## UnivariateDistribution, UncondNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asSemivar,
+## UnivariateDistribution, Neighborhood, onesidedBias':
+getAsRisk(risk, L2deriv, neighbor, biastype,
+ clip, cent, stand, trafo)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"asRisk"</code>. </td></tr>
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability distributions. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivDistrSymm</code></td>
+<td>
+object of class <code>"DistrSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The asymptotic risk is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "BiasType":</dt><dd>computes asymptotic mean square error in methods for
+function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "BiasType":</dt><dd>computes asymptotic mean square error in methods for
+function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes standardized asymptotic bias in methods for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic covariance in methods for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":</dt><dd>computes trace of asymptotic covariance in methods
+for function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":</dt><dd>computes trace of asymptotic covariance in methods for
+function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":</dt><dd>computes asymptotic under-/overshoot risk in methods for
+function <code>getInfRobIC</code>. </dd>
+
+
+<dt>risk = "asSemivar", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "onesidedBias":</dt><dd>computes asymptotic semivariance in methods for
+function <code>getInfRobIC</code>. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics & Decisions (submitted).
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/asRisk-class.html">asRisk-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getBiasIC.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getBiasIC.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getBiasIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,147 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic function for the computation of the asymptotic bias for an IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getBiasIC {ROptEst}"><tr><td>getBiasIC {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic function for the computation of the asymptotic bias for an IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the asymptotic bias for an IC.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getBiasIC(IC, neighbor, L2Fam, biastype, ...)
+
+## S4 method for signature 'IC, ContNeighborhood, missing,
+## BiasType':
+getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, ContNeighborhood,
+## L2ParamFamily, BiasType':
+getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, TotalVarNeighborhood,
+## missing, BiasType':
+getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, TotalVarNeighborhood,
+## L2ParamFamily, BiasType':
+getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+To make sure that the results are valid, it is recommended
+to include an additional check of the IC properties of <code>IC</code>
+using <code>checkIC</code>.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The asymptotic bias of an IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+</p>
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> in case of convex contamination neighborhoods
+and symmetric bias. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code>
+in case of convex contamination neighborhoods and symmetric bias. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> in case of total variation neighborhoods
+and symmetric bias. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+biastype = "BiasType"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code>
+in case of total variation neighborhoods and symmetric bias. </dd>
+</dl>
+
+<h3>Note</h3>
+
+<p>
+This generic function is still under construction.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a href="../../RobAStBase/html/InfRobModel-class.html">InfRobModel-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getFiRisk.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getFiRisk.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getFiRisk.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,126 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for Computation of Finite-Sample Risks</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getFiRisk {ROptEst}"><tr><td>getFiRisk {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for Computation of Finite-Sample Risks</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of finite-sample risks.
+This function is rarely called directly. It is used by
+other functions.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getFiRisk(risk, Distr, neighbor, ...)
+
+## S4 method for signature 'fiUnOvShoot, Norm,
+## ContNeighborhood':
+getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
+
+## S4 method for signature 'fiUnOvShoot, Norm,
+## TotalVarNeighborhood':
+getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+positive real: clipping bound </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing constant/matrix. </td></tr>
+<tr valign="top"><td><code>sampleSize</code></td>
+<td>
+integer: sample size. </td></tr>
+<tr valign="top"><td><code>Algo</code></td>
+<td>
+"A" or "B". </td></tr>
+<tr valign="top"><td><code>cont</code></td>
+<td>
+"left" or "right". </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the finite-sample under-/overshoot risk
+is based on FFT. For more details we refer to Section 11.3 of Kohl (2005).
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The finite-sample risk is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>risk = "fiUnOvShoot", Distr = "Norm", neighbor = "ContNeighborhood"</dt><dd>computes finite-sample under-/overshoot risk in methods for
+function <code>getFixRobIC</code>. </dd>
+
+
+<dt>risk = "fiUnOvShoot", Distr = "Norm", neighbor = "TotalVarNeighborhood"</dt><dd>computes finite-sample under-/overshoot risk in methods for
+function <code>getFixRobIC</code>. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+of M-estimators on Neighborhoods.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/fiRisk-class.html">fiRisk-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getFixClip.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getFixClip.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getFixClip.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,98 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of the Optimal Clipping Bound</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getFixClip {ROptEst}"><tr><td>getFixClip {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of the Optimal Clipping Bound</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the optimal clipping bound
+in case of robust models with fixed neighborhoods. This function is
+rarely called directly. It is used to compute optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getFixClip(clip, Distr, risk, neighbor, ...)
+
+## S4 method for signature 'numeric, Norm, fiUnOvShoot,
+## ContNeighborhood':
+getFixClip(clip, Distr, risk, neighbor)
+
+## S4 method for signature 'numeric, Norm, fiUnOvShoot,
+## TotalVarNeighborhood':
+getFixClip(clip, Distr, risk, neighbor)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>clip</code></td>
+<td>
+positive real: clipping bound </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The optimal clipping bound is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>clip = "numeric", Distr = "Norm", risk = "fiUnOvShoot", neighbor = "ContNeighborhood"</dt><dd>optimal clipping bound for finite-sample under-/overshoot risk. </dd>
+
+
+<dt>clip = "numeric", Distr = "Norm", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood"</dt><dd>optimal clipping bound for finite-sample under-/overshoot risk. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/ContIC-class.html">ContIC-class</a></code>, <code><a href="../../RobAStBase/html/TotalVarIC-class.html">TotalVarIC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getFixRobIC.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getFixRobIC.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getFixRobIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,111 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of Optimally Robust ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getFixRobIC {ROptEst}"><tr><td>getFixRobIC {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of Optimally Robust ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of optimally robust ICs
+in case of robust models with fixed neighborhoods. This function is
+rarely called directly.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getFixRobIC(Distr, risk, neighbor, ...)
+
+## S4 method for signature 'Norm, fiUnOvShoot,
+## UncondNeighborhood':
+getFixRobIC(Distr, risk, neighbor,
+ sampleSize, upper, maxiter, tol, warn, Algo, cont)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>sampleSize</code></td>
+<td>
+integer: sample size. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+<tr valign="top"><td><code>Algo</code></td>
+<td>
+"A" or "B". </td></tr>
+<tr valign="top"><td><code>cont</code></td>
+<td>
+"left" or "right". </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The optimally robust IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>Distr = "Norm", risk = "fiUnOvShoot", neighbor = "UncondNeighborhood"</dt><dd>computes the optimally robust influence curve for one-dimensional
+normal location and finite-sample under-/overshoot risk. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/FixRobModel-class.html">FixRobModel-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getIneffDiff.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getIneffDiff.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getIneffDiff.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,137 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of Inefficiency Differences</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getIneffDiff {ROptEst}"><tr><td>getIneffDiff {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of Inefficiency Differences</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of inefficiency differencies.
+This function is rarely called directly. It is used to compute
+the radius minimax IC and the least favorable radius.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getIneffDiff(radius, L2Fam, neighbor, risk, biastype, ...)
+
+## S4 method for signature 'numeric, L2ParamFamily,
+## UncondNeighborhood, asMSE, BiasType':
+getIneffDiff(
+ radius, L2Fam, neighbor, risk, biastype = symmetricBias(), loRad, upRad,
+ loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>radius</code></td>
+<td>
+neighborhood radius. </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2-differentiable family of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>loRad</code></td>
+<td>
+the lower end point of the interval to be searched. </td></tr>
+<tr valign="top"><td><code>upRad</code></td>
+<td>
+the upper end point of the interval to be searched. </td></tr>
+<tr valign="top"><td><code>loRisk</code></td>
+<td>
+the risk at the lower end point of the interval. </td></tr>
+<tr valign="top"><td><code>upRisk</code></td>
+<td>
+the risk at the upper end point of the interval. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>upper.b</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>MaxIter</code></td>
+<td>
+the maximum number of iterations </td></tr>
+<tr valign="top"><td><code>eps</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The inefficieny difference between the left and
+the right margin of a given radius interval is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>radius = "numeric", L2Fam = "L2ParamFamily",
+neighbor = "UncondNeighborhood", risk = "asMSE", biastype = "BiasType":</dt><dd>computes difference of asymptotic MSE–inefficiency for
+the boundaries of a given radius interval.</dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="radiusMinimaxIC.html">radiusMinimaxIC</a></code>, <code><a href="leastFavorableRadius.html">leastFavorableRadius</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getInfCent.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getInfCent.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getInfCent.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,150 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getInfCent {ROptEst}"><tr><td>getInfCent {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the optimal centering constant
+(contamination neighborhoods) respectively, of the optimal lower clipping
+bound (total variation neighborhood).
+This function is rarely called directly. It is used to
+compute optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getInfCent(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, onesidedBias':
+getInfCent(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+getInfCent(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>tol.z</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>symm</code></td>
+<td>
+logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+<tr valign="top"><td><code>z.comp</code></td>
+<td>
+logical vector: indication which components of the
+centering constant have to be computed. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The optimal centering constant is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType"</dt><dd>computation of optimal centering constant for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType"</dt><dd>computation of optimal lower clipping bound for symmetric bias. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType"</dt><dd>computation of optimal centering constant for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias"</dt><dd>computation of optimal centering constant for onesided bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias"</dt><dd>computation of optimal centering constant for asymmetric bias. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/ContIC-class.html">ContIC-class</a></code>, <code><a href="../../RobAStBase/html/TotalVarIC-class.html">TotalVarIC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getInfClip.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getInfClip.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getInfClip.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,151 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of the Optimal Clipping Bound</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getInfClip {ROptEst}"><tr><td>getInfClip {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of the Optimal Clipping Bound</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the optimal clipping bound
+in case of infinitesimal robust models. This function is rarely called
+directly. It is used to compute optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getInfClip(clip, L2deriv, risk, neighbor, ...)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asMSE, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asMSE, TotalVarNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric, EuclRandVariable,
+## asMSE, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, Distr, stand, biastype, cent, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asUnOvShoot,
+## UncondNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asSemivar, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>clip</code></td>
+<td>
+positive real: clipping bound </td></tr>
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>symm</code></td>
+<td>
+logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The optimal clipping bound is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asMSE", neighbor = "ContNeighborhood"</dt><dd>optimal clipping bound for asymtotic mean square error. </dd>
+
+
+<dt>clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asMSE", neighbor = "TotalVarNeighborhood"</dt><dd>optimal clipping bound for asymtotic mean square error. </dd>
+
+
+<dt>clip = "numeric", L2deriv = "EuclRandVariable",
+risk = "asMSE", neighbor = "ContNeighborhood"</dt><dd>optimal clipping bound for asymtotic mean square error. </dd>
+
+
+<dt>clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asUnOvShoot", neighbor = "UncondNeighborhood"</dt><dd>optimal clipping bound for asymtotic under-/overshoot risk. </dd>
+
+
+<dt>clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asSemivar", neighbor = "ContNeighborhood"</dt><dd>optimal clipping bound for asymtotic semivariance.</dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/ContIC-class.html">ContIC-class</a></code>, <code><a href="../../RobAStBase/html/TotalVarIC-class.html">TotalVarIC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getInfGamma.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getInfGamma.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getInfGamma.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,173 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of the Optimal Clipping Bound</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getInfGamma {ROptEst}"><tr><td>getInfGamma {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of the Optimal Clipping Bound</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the optimal clipping bound.
+This function is rarely called directly. It is called by <code>getInfClip</code>
+to compute optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getInfGamma(L2deriv, risk, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## asGRisk, TotalVarNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'RealRandVariable, asMSE,
+## ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## asUnOvShoot, ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, onesidedBias':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = positiveBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, asymmetricBias':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = asymmetricBias(), cent, clip)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The function is used in case of asymptotic G-risks; confer
+Ruckdeschel and Rieder (2004).
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asGRisk",
+neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",
+neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>used by <code>getInfClip</code> for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "onesidedBias"</dt><dd>used by <code>getInfClip</code> for onesided bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"</dt><dd>used by <code>getInfClip</code> for asymmetric bias. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics & Decisions <EM>22</EM>, 201-223.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/asGRisk-class.html">asGRisk-class</a></code>, <code><a href="../../distrMod/html/asMSE-class.html">asMSE-class</a></code>,
+<code><a href="../../distrMod/html/asUnOvShoot-class.html">asUnOvShoot-class</a></code>, <code><a href="../../RobAStBase/html/ContIC-class.html">ContIC-class</a></code>,
+<code><a href="../../RobAStBase/html/TotalVarIC-class.html">TotalVarIC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getInfRobIC.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getInfRobIC.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getInfRobIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,236 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of Optimally Robust ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getInfRobIC {ROptEst}"><tr><td>getInfRobIC {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of Optimally Robust ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of optimally robust ICs
+in case of infinitesimal robust models. This function is
+rarely called directly.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getInfRobIC(L2deriv, risk, neighbor, ...)
+
+## S4 method for signature 'UnivariateDistribution, asCov,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
+
+## S4 method for signature 'UnivariateDistribution, asCov,
+## TotalVarNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
+
+## S4 method for signature 'RealRandVariable, asCov,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo)
+
+## S4 method for signature 'UnivariateDistribution, asBias,
+## UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable, asBias,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## asHampel, UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable, asHampel,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## asGRisk, UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable, asGRisk,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## asUnOvShoot, UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>symm</code></td>
+<td>
+logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
+<tr valign="top"><td><code>DistrSymm</code></td>
+<td>
+object of class <code>"DistributionSymmetry"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivSymm</code></td>
+<td>
+object of class <code>"FunSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivDistrSymm</code></td>
+<td>
+object of class <code>"DistrSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>Finfo</code></td>
+<td>
+Fisher information matrix. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The optimally robust IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2deriv = "UnivariateDistribution", risk = "asCov",
+neighbor = "ContNeighborhood"</dt><dd>computes the classical optimal influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asCov",
+neighbor = "TotalVarNeighborhood"</dt><dd>computes the classical optimal influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", risk = "asCov",
+neighbor = "ContNeighborhood"</dt><dd>computes the classical optimal influence curve for L2 differentiable
+parametric families with unknown <i>k</i>-dimensional parameter
+(<i>k > 1</i>) where the underlying distribution is univariate. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asBias",
+neighbor = "UncondNeighborhood"</dt><dd>computes the bias optimal influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", risk = "asBias",
+neighbor = "ContNeighborhood"</dt><dd>computes the bias optimal influence curve for L2 differentiable
+parametric families with unknown <i>k</i>-dimensional parameter
+(<i>k > 1</i>) where the underlying distribution is univariate. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asHampel",
+neighbor = "UncondNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", risk = "asHampel",
+neighbor = "ContNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown <i>k</i>-dimensional parameter
+(<i>k > 1</i>) where the underlying distribution is univariate. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asGRisk",
+neighbor = "UncondNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", risk = "asGRisk",
+neighbor = "ContNeighborhood"</dt><dd>computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown <i>k</i>-dimensional parameter
+(<i>k > 1</i>) where the underlying distribution is univariate. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",
+neighbor = "UncondNeighborhood"</dt><dd>computes the optimally robust influence curve for one-dimensional
+L2 differentiable parametric families and
+asymptotic under-/overshoot risk. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106-115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics & Decisions <B>22</B>: 201-223.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/InfRobModel-class.html">InfRobModel-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getInfStand.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getInfStand.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getInfStand.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,150 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of the Standardizing Matrix</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getInfStand {ROptEst}"><tr><td>getInfStand {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of the Standardizing Matrix</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the standardizing matrix which
+takes care of the Fisher consistency of the corresponding IC. This function
+is rarely called directly. It is used to compute optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getInfStand(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, trafo)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code> </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+optimal centering constant. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing matrix. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+<tr valign="top"><td><code>A.comp</code></td>
+<td>
+matrix: indication which components of the standardizing
+matrix have to be computed. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The standardizing matrix is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes standardizing matrix for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"</dt><dd>computes standardizing matrix for symmetric bias. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes standardizing matrix for symmetric bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "onesidedBias"</dt><dd>computes standardizing matrix for onesided bias. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"</dt><dd>computes standardizing matrix for asymmetric bias. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/ContIC-class.html">ContIC-class</a></code>, <code><a href="../../RobAStBase/html/TotalVarIC-class.html">TotalVarIC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getL1normL2deriv.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getL1normL2deriv.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getL1normL2deriv.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,74 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Calculation of L1 norm of L2derivative</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getL1normL2deriv {ROptEst}"><tr><td>getL1normL2deriv {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Calculation of L1 norm of L2derivative</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Methods to calculate the L1 norm of the L2derivative in a smooth parametric model.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>getL1normL2deriv(L2deriv, ...)
+## S4 method for signature 'UnivariateDistribution':
+getL1normL2deriv(L2deriv,
+ cent, ...)
+
+## S4 method for signature 'UnivariateDistribution':
+getL1normL2deriv(L2deriv,
+ cent, stand, Distr, ...)
+
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2derivative of the model</td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+centering Lagrange Multiplier</td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+standardizing Lagrange Multiplier</td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+distribution of the L2derivative</td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+further arguments (not used at the moment)</td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+L1 norm of the L2derivative</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+##
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getL2normL2deriv.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getL2normL2deriv.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getL2normL2deriv.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,59 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Calculation of L2 norm of L2derivative</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getL2normL2deriv {ROptEst}"><tr><td>getL2normL2deriv {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Calculation of L2 norm of L2derivative</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Function to calculate the L2 norm of the L2derivative in a smooth parametric model.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>getL2normL2deriv(aFinfo, cent, ...)</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>aFinfo</code></td>
+<td>
+trace of the Fisher information</td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+centering</td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+further arguments (not used at the moment)</td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+L2 norm of the L2derivative</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+##
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/getRiskIC.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/getRiskIC.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/getRiskIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,205 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic function for the computation of a risk for an IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for getRiskIC {ROptEst}"><tr><td>getRiskIC {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic function for the computation of a risk for an IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of a risk for an IC.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+getRiskIC(IC, risk, neighbor, L2Fam, ...)
+
+## S4 method for signature 'IC, asCov, missing, missing':
+getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asCov, missing,
+## L2ParamFamily':
+getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, trAsCov, missing, missing':
+getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, trAsCov, missing,
+## L2ParamFamily':
+getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## missing':
+getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## L2ParamFamily':
+getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+## missing':
+getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+## L2ParamFamily':
+getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'TotalVarIC, asUnOvShoot,
+## UncondNeighborhood, missing':
+getRiskIC(IC, risk, neighbor)
+
+## S4 method for signature 'IC, fiUnOvShoot,
+## ContNeighborhood, missing':
+getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+
+## S4 method for signature 'IC, fiUnOvShoot,
+## TotalVarNeighborhood, missing':
+getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+object of class <code>"L2ParamFamily"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>sampleSize</code></td>
+<td>
+integer: sample size. </td></tr>
+<tr valign="top"><td><code>Algo</code></td>
+<td>
+"A" or "B". </td></tr>
+<tr valign="top"><td><code>cont</code></td>
+<td>
+"left" or "right". </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+To make sure that the results are valid, it is recommended
+to include an additional check of the IC properties of <code>IC</code>
+using <code>checkIC</code>.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The risk of an IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "missing"</dt><dd>asymptotic covariance of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "L2ParamFamily"</dt><dd>asymptotic covariance of <code>IC</code> under <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing"</dt><dd>asymptotic bias of <code>IC</code> under convex contaminations. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic bias of <code>IC</code> under convex contaminations and <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing"</dt><dd>asymptotic bias of <code>IC</code> in case of total variation neighborhoods. </dd>
+
+
+<dt>IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic bias of <code>IC</code> under <code>L2Fam</code> in case of total variation
+neighborhoods. </dd>
+
+
+<dt>IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "missing"</dt><dd>asymptotic mean square error of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "L2ParamFamily"</dt><dd>asymptotic mean square error of <code>IC</code> under <code>L2Fam</code>. </dd>
+
+
+<dt>IC = "TotalVarIC", risk = "asUnOvShoot", neighbor = "UncondNeighborhood", L2Fam = "missing"</dt><dd>asymptotic under-/overshoot risk of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "fiUnOvShoot", neighbor = "ContNeighborhood", L2Fam = "missing"</dt><dd>finite-sample under-/overshoot risk of <code>IC</code>. </dd>
+
+
+<dt>IC = "IC", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood", L2Fam = "missing"</dt><dd>finite-sample under-/overshoot risk of <code>IC</code>. </dd>
+</dl>
+
+<h3>Note</h3>
+
+<p>
+This generic function is still under construction.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+of M-estimators on Neighborhoods.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="getRiskIC.html">getRiskIC-methods</a></code>, <code><a href="../../RobAStBase/html/InfRobModel-class.html">InfRobModel-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/leastFavorableRadius.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/leastFavorableRadius.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/leastFavorableRadius.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,140 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of Least Favorable Radii</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for leastFavorableRadius {ROptEst}"><tr><td>leastFavorableRadius {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of Least Favorable Radii</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of least favorable radii.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+leastFavorableRadius(L2Fam, neighbor, risk, ...)
+
+## S4 method for signature 'L2ParamFamily,
+## UncondNeighborhood, asGRisk':
+leastFavorableRadius(
+ L2Fam, neighbor, risk, biastype = symmetricBias(), rho, upRad = 1,
+ z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
+ tol = .Machine$double.eps^0.4, warn = FALSE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2-differentiable family of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>upRad</code></td>
+<td>
+the upper end point of the radius interval to be searched. </td></tr>
+<tr valign="top"><td><code>rho</code></td>
+<td>
+The considered radius interval is: <i>[r*rho, r/rho]</i>
+with <i>0 < rho < 1</i>. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The least favorable radius and the corresponding inefficiency
+are computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood",
+risk = "asGRisk"</dt><dd>computation of the least favorable radius. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+the Radius. Statistical Methods and Applications <EM>17</EM>(1) 13-40.
+</p>
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="radiusMinimaxIC.html">radiusMinimaxIC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+N <- NormLocationFamily(mean=0, sd=1)
+leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5)
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/locMEstimator.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/locMEstimator.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/locMEstimator.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,94 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic function for the computation of location M estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for locMEstimator {ROptEst}"><tr><td>locMEstimator {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic function for the computation of location M estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of location M estimators.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+locMEstimator(x, IC, ...)
+
+## S4 method for signature 'numeric, InfluenceCurve':
+locMEstimator(x, IC, eps = .Machine$double.eps^0.5)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>x</code></td>
+<td>
+sample </td></tr>
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>eps</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Returns a list with component
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>loc</code></td>
+<td>
+M estimator of location </td></tr>
+</table>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>x = "numeric", IC = "InfluenceCurve"</dt><dd>univariate location. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1964) Robust estimation of a location parameter.
+Ann. Math. Stat. <B>35</B>: 73–101.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/InfluenceCurve-class.html">InfluenceCurve-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/lowerCaseRadius.html
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--- pkg/ROptEst.Rcheck/ROptEst/html/lowerCaseRadius.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/lowerCaseRadius.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,102 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Computation of the lower case radius</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for lowerCaseRadius {ROptEst}"><tr><td>lowerCaseRadius {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Computation of the lower case radius</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The lower case radius is computed; confer Subsection 2.1.2
+in Kohl (2005) and formula (4.5) in Ruckdeschel (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+lowerCaseRadius(L2Fam, neighbor, risk, biastype, ...)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2 differentiable parametric family </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code> </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code> </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+lower case radius</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE",
+biastype = "BiasType"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"ContNeighborhood"</code>
+for symmetric bias.</dd>
+
+
+<dt>L2Fam = "L2ParamFamily", neighbor = "TotalVarNeighborhood", risk = "asMSE",
+biastype = "BiasType"</dt><dd>lower case radius for risk <code>"asMSE"</code> in case of <code>"TotalVarNeighborhood"</code>;
+(argument biastype is just for signature reasons).</dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/L2ParamFamily-class.html">L2ParamFamily-class</a></code>, <code><a href="../../RobAStBase/html/Neighborhood-class.html">Neighborhood-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+lowerCaseRadius(BinomFamily(size = 10), ContNeighborhood(), asMSE())
+lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/minmaxBias.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/minmaxBias.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/minmaxBias.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,172 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic Function for the Computation of Bias-Optimally Robust ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for minmaxBias {ROptEst}"><tr><td>minmaxBias {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic Function for the Computation of Bias-Optimally Robust ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of bias-optimally robust ICs
+in case of infinitesimal robust models. This function is
+rarely called directly.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+minmaxBias(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+minmaxBias(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2deriv</code></td>
+<td>
+L2-derivative of some L2-differentiable family
+of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>Distr</code></td>
+<td>
+object of class <code>"Distribution"</code>. </td></tr>
+<tr valign="top"><td><code>symm</code></td>
+<td>
+logical: indicating symmetry of <code>L2deriv</code>. </td></tr>
+<tr valign="top"><td><code>DistrSymm</code></td>
+<td>
+object of class <code>"DistributionSymmetry"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivSymm</code></td>
+<td>
+object of class <code>"FunSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>L2derivDistrSymm</code></td>
+<td>
+object of class <code>"DistrSymmList"</code>. </td></tr>
+<tr valign="top"><td><code>Finfo</code></td>
+<td>
+Fisher information matrix. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>trafo</code></td>
+<td>
+matrix: transformation of the parameter. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The bias-optimally robust IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"</dt><dd>computes the bias optimal influence curve for asymmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter. </dd>
+
+
+<dt>L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+biastype = "BiasType"</dt><dd>computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown <i>k</i>-dimensional parameter
+(<i>k > 1</i>) where the underlying distribution is univariate. </dd>
+
+<p>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics <EM>14</EM>(1), 105-131.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/InfRobModel-class.html">InfRobModel-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/optIC.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/optIC.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/optIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,171 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic function for the computation of optimally robust ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for optIC {ROptEst}"><tr><td>optIC {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic function for the computation of optimally robust ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+optIC(model, risk, ...)
+
+## S4 method for signature 'L2ParamFamily, asCov':
+optIC(model, risk)
+
+## S4 method for signature 'InfRobModel, asRisk':
+optIC(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
+## S4 method for signature 'InfRobModel, asUnOvShoot':
+optIC(model, risk, biastype = symmetricBias(),
+ upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE)
+
+## S4 method for signature 'FixRobModel, fiUnOvShoot':
+optIC(model, risk, sampleSize, upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>model</code></td>
+<td>
+probability model. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code> </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+<tr valign="top"><td><code>sampleSize</code></td>
+<td>
+integer: sample size. </td></tr>
+<tr valign="top"><td><code>Algo</code></td>
+<td>
+"A" or "B". </td></tr>
+<tr valign="top"><td><code>cont</code></td>
+<td>
+"left" or "right". </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+In case of the finite-sample risk <code>"fiUnOvShoot"</code> one can choose
+between two algorithms for the computation of this risk where the least favorable
+contamination is assumed to be left or right of some bound. For more details
+we refer to Section 11.3 of Kohl (2005).
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Some optimally robust IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>model = "L2ParamFamily", risk = "asCov"</dt><dd>computes
+classical optimal influence curve for L2 differentiable
+parametric families.</dd>
+
+
+<dt>model = "InfRobModel", risk = "asRisk"</dt><dd>computes optimally robust influence curve for
+robust models with infinitesimal neighborhoods and
+various asymptotic risks. </dd>
+
+
+<dt>model = "InfRobModel", risk = "asUnOvShoot"</dt><dd>computes optimally robust influence curve for
+robust models with infinitesimal neighborhoods and
+asymptotic under-/overshoot risk. </dd>
+
+
+<dt>model = "FixRobModel", risk = "fiUnOvShoot"</dt><dd>computes optimally robust influence curve for
+robust models with fixed neighborhoods and
+finite-sample under-/overshoot risk. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../RobAStBase/html/InfluenceCurve-class.html">InfluenceCurve-class</a></code>, <code><a href="../../distrMod/html/RiskType-class.html">RiskType-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+B <- BinomFamily(size = 25, prob = 0.25)
+
+## classical optimal IC
+IC0 <- optIC(model = B, risk = asCov())
+plot(IC0) # plot IC
+checkIC(IC0, B)
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/optRisk.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/optRisk.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/optRisk.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,153 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic function for the computation of the minimal risk</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for optRisk {ROptEst}"><tr><td>optRisk {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic function for the computation of the minimal risk</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the optimal (i.e., minimal)
+risk for a probability model.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+optRisk(model, risk, ...)
+
+## S4 method for signature 'L2ParamFamily, asCov':
+optRisk(model, risk)
+
+## S4 method for signature 'InfRobModel, asRisk':
+optRisk(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
+## S4 method for signature 'FixRobModel, fiUnOvShoot':
+optRisk(model, risk, sampleSize, upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>model</code></td>
+<td>
+probability model </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>RiskType</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>BiasType</code> </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+<tr valign="top"><td><code>sampleSize</code></td>
+<td>
+integer: sample size. </td></tr>
+<tr valign="top"><td><code>Algo</code></td>
+<td>
+"A" or "B". </td></tr>
+<tr valign="top"><td><code>cont</code></td>
+<td>
+"left" or "right". </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+In case of the finite-sample risk <code>"fiUnOvShoot"</code> one can choose
+between two algorithms for the computation of this risk where the least favorable
+contamination is assumed to be left or right of some bound. For more details
+we refer to Section 11.3 of Kohl (2005).
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The minimal risk is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>model = "L2ParamFamily", risk = "asCov"</dt><dd>asymptotic covariance of L2 differentiable parameteric
+family. </dd>
+
+
+<dt>model = "InfRobModel", risk = "asRisk"</dt><dd>asymptotic risk of a infinitesimal robust model. </dd>
+
+
+<dt>model = "FixRobModel", risk = "fiUnOvShoot"</dt><dd>finite-sample under-/overshoot risk of a robust model
+with fixed neighborhood. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. <B>10</B>:269–278.
+</p>
+<p>
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. <B>8</B>: 106–115.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/RiskType-class.html">RiskType-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+optRisk(model = NormLocationScaleFamily(), risk = asCov())
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/radiusMinimaxIC.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/radiusMinimaxIC.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/radiusMinimaxIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,129 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Generic function for the computation of the radius minimax IC</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for radiusMinimaxIC {ROptEst}"><tr><td>radiusMinimaxIC {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Generic function for the computation of the radius minimax IC</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of the radius minimax IC.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+radiusMinimaxIC(L2Fam, neighbor, risk, ...)
+
+## S4 method for signature 'L2ParamFamily,
+## UncondNeighborhood, asGRisk':
+radiusMinimaxIC(
+ L2Fam, neighbor, risk, biastype = symmetricBias(),
+ loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
+ maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2-differentiable family of probability measures. </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+<tr valign="top"><td><code>biastype</code></td>
+<td>
+object of class <code>"BiasType"</code>. </td></tr>
+<tr valign="top"><td><code>loRad</code></td>
+<td>
+the lower end point of the interval to be searched. </td></tr>
+<tr valign="top"><td><code>upRad</code></td>
+<td>
+the upper end point of the interval to be searched. </td></tr>
+<tr valign="top"><td><code>z.start</code></td>
+<td>
+initial value for the centering constant. </td></tr>
+<tr valign="top"><td><code>A.start</code></td>
+<td>
+initial value for the standardizing matrix. </td></tr>
+<tr valign="top"><td><code>upper</code></td>
+<td>
+upper bound for the optimal clipping bound. </td></tr>
+<tr valign="top"><td><code>maxiter</code></td>
+<td>
+the maximum number of iterations </td></tr>
+<tr valign="top"><td><code>tol</code></td>
+<td>
+the desired accuracy (convergence tolerance).</td></tr>
+<tr valign="top"><td><code>warn</code></td>
+<td>
+logical: print warnings. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+The radius minimax IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asGRisk":</dt><dd>computation of the radius minimax IC for an L2 differentiable parametric family. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>,
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="radiusMinimaxIC.html">radiusMinimaxIC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+N <- NormLocationFamily(mean=0, sd=1)
+radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5)
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/trAsCov-class.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/trAsCov-class.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/trAsCov-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,77 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Trace of asymptotic covariance</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for trAsCov-class {ROptEst}"><tr><td>trAsCov-class {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Trace of asymptotic covariance</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of trace of asymptotic covariance.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("trAsCov", ...)</code>.
+More frequently they are created via the generating function
+<code>trAsCov</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
+“trace of asymptotic covariance”. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"asRisk"</code>, directly.<br>
+Class <code>"RiskType"</code>, by class <code>"asRisk"</code>.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/asRisk-class.html">asRisk-class</a></code>, <code><a href="../../distrMod/html/trAsCov.html">trAsCov</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("trAsCov")
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/html/trFiCov-class.html
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/html/trFiCov-class.html (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/html/trFiCov-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,74 @@
+<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html><head><title>R: Trace of finite-sample covariance</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="../../R.css">
+</head><body>
+
+<table width="100%" summary="page for trFiCov-class {ROptEst}"><tr><td>trFiCov-class {ROptEst}</td><td align="right">R Documentation</td></tr></table>
+<h2>Trace of finite-sample covariance</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of trace of finite-sample covariance.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("trFiCov", ...)</code>.
+More frequently they are created via the generating function
+<code>trFiCov</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
+“trace of finite-sample covariance”. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"fiRisk"</code>, directly.<br>
+Class <code>"RiskType"</code>, by class <code>"fiRisk"</code>.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Ruckdeschel, P. and Kohl, M. (2005) How to approximate
+the finite sample risk of M-estimators.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="../../distrMod/html/fiRisk-class.html">fiRisk-class</a></code>, <code><a href="../../distrMod/html/trFiCov.html">trFiCov</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("trFiCov")
+</pre>
+
+
+
+<hr><div align="center">[Package <em>ROptEst</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getAsRisk.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getAsRisk.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getAsRisk.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,146 @@
+\HeaderA{getAsRisk}{Generic Function for Computation of Asymptotic Risks}{getAsRisk}
+\aliasA{getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asBias,RealRandVariable,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asBias,UnivariateDistribution,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asBias,UnivariateDistribution,TotalVarNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asCov,RealRandVariable,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asCov,UnivariateDistribution,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asCov,UnivariateDistribution,TotalVarNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType-method}{getAsRisk}{getAsRisk,asMSE,EuclRandVariable,Neighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType-method}{getAsRisk}{getAsRisk,asMSE,UnivariateDistribution,Neighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias-method}{getAsRisk}{getAsRisk,asSemivar,UnivariateDistribution,Neighborhood,onesidedBias.Rdash.method}
+\aliasA{getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,asUnOvShoot,UnivariateDistribution,UncondNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,trAsCov,RealRandVariable,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType-method}{getAsRisk}{getAsRisk,trAsCov,UnivariateDistribution,UncondNeighborhood,BiasType.Rdash.method}
+\aliasA{getAsRisk-methods}{getAsRisk}{getAsRisk.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of asymptotic risks.
+This function is rarely called directly. It is used by
+other functions.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getAsRisk(risk, L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'asMSE, UnivariateDistribution,
+## Neighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asMSE, EuclRandVariable,
+## Neighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asBias, UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
+
+## S4 method for signature 'asBias, UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, trafo)
+
+## S4 method for signature 'asBias, RealRandVariable,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, L2derivDistrSymm, trafo,
+ z.start, A.start, maxiter, tol)
+
+## S4 method for signature 'asCov, UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+## S4 method for signature 'asCov, UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+## S4 method for signature 'asCov, RealRandVariable,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+
+## S4 method for signature 'trAsCov,
+## UnivariateDistribution, UncondNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+
+## S4 method for signature 'trAsCov, RealRandVariable,
+## ContNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+
+## S4 method for signature 'asUnOvShoot,
+## UnivariateDistribution, UncondNeighborhood, BiasType':
+getAsRisk(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+
+## S4 method for signature 'asSemivar,
+## UnivariateDistribution, Neighborhood, onesidedBias':
+getAsRisk(risk, L2deriv, neighbor, biastype,
+ clip, cent, stand, trafo)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{risk}] object of class \code{"asRisk"}.
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability distributions.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{...}] additional parameters.
+\item[\code{clip}] optimal clipping bound.
+\item[\code{cent}] optimal centering constant.
+\item[\code{stand}] standardizing matrix.
+\item[\code{trafo}] matrix: transformation of the parameter.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{L2derivDistrSymm}] object of class \code{"DistrSymmList"}.
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{maxiter}] the maximum number of iterations
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The asymptotic risk is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[risk = "asMSE", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "BiasType":] computes asymptotic mean square error in methods for
+function \code{getInfRobIC}.
+
+\item[risk = "asMSE", L2deriv = "EuclRandVariable", neighbor = "Neighborhood", biastype = "BiasType":] computes asymptotic mean square error in methods for
+function \code{getInfRobIC}.
+
+\item[risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":] computes standardized asymptotic bias in methods for function \code{getInfRobIC}.
+
+\item[risk = "asBias", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":] computes standardized asymptotic bias in methods for function \code{getInfRobIC}.
+
+\item[risk = "asBias", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":] computes standardized asymptotic bias in methods for function \code{getInfRobIC}.
+
+\item[risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType":] computes asymptotic covariance in methods for function \code{getInfRobIC}.
+
+\item[risk = "asCov", L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType":] computes asymptotic covariance in methods for function \code{getInfRobIC}.
+
+\item[risk = "asCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":] computes asymptotic covariance in methods for function \code{getInfRobIC}.
+
+\item[risk = "trAsCov", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":] computes trace of asymptotic covariance in methods
+for function \code{getInfRobIC}.
+
+\item[risk = "trAsCov", L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType":] computes trace of asymptotic covariance in methods for
+function \code{getInfRobIC}.
+
+\item[risk = "asUnOvShoot", L2deriv = "UnivariateDistribution", neighbor = "UncondNeighborhood", biastype = "BiasType":] computes asymptotic under-/overshoot risk in methods for
+function \code{getInfRobIC}.
+
+\item[risk = "asSemivar", L2deriv = "UnivariateDistribution", neighbor = "Neighborhood", biastype = "onesidedBias":] computes asymptotic semivariance in methods for
+function \code{getInfRobIC}.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics \& Decisions (submitted).
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{asRisk-class}{asRisk.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getBiasIC.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getBiasIC.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getBiasIC.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,92 @@
+\HeaderA{getBiasIC}{Generic function for the computation of the asymptotic bias for an IC}{getBiasIC}
+\aliasA{getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType-method}{getBiasIC}{getBiasIC,IC,ContNeighborhood,L2ParamFamily,BiasType.Rdash.method}
+\aliasA{getBiasIC,IC,ContNeighborhood,missing,BiasType-method}{getBiasIC}{getBiasIC,IC,ContNeighborhood,missing,BiasType.Rdash.method}
+\aliasA{getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType-method}{getBiasIC}{getBiasIC,IC,TotalVarNeighborhood,L2ParamFamily,BiasType.Rdash.method}
+\aliasA{getBiasIC,IC,TotalVarNeighborhood,missing,BiasType-method}{getBiasIC}{getBiasIC,IC,TotalVarNeighborhood,missing,BiasType.Rdash.method}
+\aliasA{getBiasIC-methods}{getBiasIC}{getBiasIC.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the asymptotic bias for an IC.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getBiasIC(IC, neighbor, L2Fam, biastype, ...)
+
+## S4 method for signature 'IC, ContNeighborhood, missing,
+## BiasType':
+getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, ContNeighborhood,
+## L2ParamFamily, BiasType':
+getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, TotalVarNeighborhood,
+## missing, BiasType':
+getBiasIC(IC, neighbor,
+ biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, TotalVarNeighborhood,
+## L2ParamFamily, BiasType':
+getBiasIC(IC, neighbor,
+ L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{IC}] object of class \code{"InfluenceCurve"}
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{L2Fam}] object of class \code{"L2ParamFamily"}.
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{...}] additional parameters
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\end{ldescription}
+\end{Arguments}
+\begin{Details}\relax
+To make sure that the results are valid, it is recommended
+to include an additional check of the IC properties of \code{IC}
+using \code{checkIC}.
+\end{Details}
+\begin{Value}
+The asymptotic bias of an IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+
+\item[IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+biastype = "BiasType"] asymptotic bias of \code{IC} in case of convex contamination neighborhoods
+and symmetric bias.
+
+\item[IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing",
+biastype = "BiasType"] asymptotic bias of \code{IC} under \code{L2Fam}
+in case of convex contamination neighborhoods and symmetric bias.
+
+\item[IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+biastype = "BiasType"] asymptotic bias of \code{IC} in case of total variation neighborhoods
+and symmetric bias.
+
+\item[IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing",
+biastype = "BiasType"] asymptotic bias of \code{IC} under \code{L2Fam}
+in case of total variation neighborhoods and symmetric bias.
+}
+\end{Section}
+\begin{Note}\relax
+This generic function is still under construction.
+\end{Note}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{getRiskIC-methods}{getRiskIC.Rdash.methods}}, \code{\LinkA{InfRobModel-class}{InfRobModel.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getFiRisk.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getFiRisk.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getFiRisk.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,70 @@
+\HeaderA{getFiRisk}{Generic Function for Computation of Finite-Sample Risks}{getFiRisk}
+\aliasA{getFiRisk,fiUnOvShoot,Norm,ContNeighborhood-method}{getFiRisk}{getFiRisk,fiUnOvShoot,Norm,ContNeighborhood.Rdash.method}
+\aliasA{getFiRisk,fiUnOvShoot,Norm,TotalVarNeighborhood-method}{getFiRisk}{getFiRisk,fiUnOvShoot,Norm,TotalVarNeighborhood.Rdash.method}
+\aliasA{getFiRisk-methods}{getFiRisk}{getFiRisk.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of finite-sample risks.
+This function is rarely called directly. It is used by
+other functions.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getFiRisk(risk, Distr, neighbor, ...)
+
+## S4 method for signature 'fiUnOvShoot, Norm,
+## ContNeighborhood':
+getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
+
+## S4 method for signature 'fiUnOvShoot, Norm,
+## TotalVarNeighborhood':
+getFiRisk(risk, Distr,
+ neighbor, clip, stand, sampleSize, Algo, cont)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{...}] additional parameters.
+\item[\code{clip}] positive real: clipping bound
+\item[\code{stand}] standardizing constant/matrix.
+\item[\code{sampleSize}] integer: sample size.
+\item[\code{Algo}] "A" or "B".
+\item[\code{cont}] "left" or "right".
+\end{ldescription}
+\end{Arguments}
+\begin{Details}\relax
+The computation of the finite-sample under-/overshoot risk
+is based on FFT. For more details we refer to Section 11.3 of Kohl (2005).
+\end{Details}
+\begin{Value}
+The finite-sample risk is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[risk = "fiUnOvShoot", Distr = "Norm", neighbor = "ContNeighborhood"] computes finite-sample under-/overshoot risk in methods for
+function \code{getFixRobIC}.
+
+\item[risk = "fiUnOvShoot", Distr = "Norm", neighbor = "TotalVarNeighborhood"] computes finite-sample under-/overshoot risk in methods for
+function \code{getFixRobIC}.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. \bold{10}:269--278.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+of M-estimators on Neighborhoods.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{fiRisk-class}{fiRisk.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getFixClip.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getFixClip.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getFixClip.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,55 @@
+\HeaderA{getFixClip}{Generic Function for the Computation of the Optimal Clipping Bound}{getFixClip}
+\aliasA{getFixClip,numeric,Norm,fiUnOvShoot,ContNeighborhood-method}{getFixClip}{getFixClip,numeric,Norm,fiUnOvShoot,ContNeighborhood.Rdash.method}
+\aliasA{getFixClip,numeric,Norm,fiUnOvShoot,TotalVarNeighborhood-method}{getFixClip}{getFixClip,numeric,Norm,fiUnOvShoot,TotalVarNeighborhood.Rdash.method}
+\aliasA{getFixClip-methods}{getFixClip}{getFixClip.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the optimal clipping bound
+in case of robust models with fixed neighborhoods. This function is
+rarely called directly. It is used to compute optimally robust ICs.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getFixClip(clip, Distr, risk, neighbor, ...)
+
+## S4 method for signature 'numeric, Norm, fiUnOvShoot,
+## ContNeighborhood':
+getFixClip(clip, Distr, risk, neighbor)
+
+## S4 method for signature 'numeric, Norm, fiUnOvShoot,
+## TotalVarNeighborhood':
+getFixClip(clip, Distr, risk, neighbor)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{clip}] positive real: clipping bound
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{...}] additional parameters.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The optimal clipping bound is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[clip = "numeric", Distr = "Norm", risk = "fiUnOvShoot", neighbor = "ContNeighborhood"] optimal clipping bound for finite-sample under-/overshoot risk.
+
+\item[clip = "numeric", Distr = "Norm", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood"] optimal clipping bound for finite-sample under-/overshoot risk.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. \bold{10}:269--278.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{ContIC-class}{ContIC.Rdash.class}}, \code{\LinkA{TotalVarIC-class}{TotalVarIC.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getFixRobIC.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getFixRobIC.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getFixRobIC.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,56 @@
+\HeaderA{getFixRobIC}{Generic Function for the Computation of Optimally Robust ICs}{getFixRobIC}
+\aliasA{getFixRobIC,Norm,fiUnOvShoot,UncondNeighborhood-method}{getFixRobIC}{getFixRobIC,Norm,fiUnOvShoot,UncondNeighborhood.Rdash.method}
+\aliasA{getFixRobIC-methods}{getFixRobIC}{getFixRobIC.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of optimally robust ICs
+in case of robust models with fixed neighborhoods. This function is
+rarely called directly.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getFixRobIC(Distr, risk, neighbor, ...)
+
+## S4 method for signature 'Norm, fiUnOvShoot,
+## UncondNeighborhood':
+getFixRobIC(Distr, risk, neighbor,
+ sampleSize, upper, maxiter, tol, warn, Algo, cont)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{...}] additional parameters.
+\item[\code{sampleSize}] integer: sample size.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations.
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\item[\code{Algo}] "A" or "B".
+\item[\code{cont}] "left" or "right".
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The optimally robust IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[Distr = "Norm", risk = "fiUnOvShoot", neighbor = "UncondNeighborhood"] computes the optimally robust influence curve for one-dimensional
+normal location and finite-sample under-/overshoot risk.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. \bold{10}:269--278.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{FixRobModel-class}{FixRobModel.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getIneffDiff.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getIneffDiff.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getIneffDiff.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,71 @@
+\HeaderA{getIneffDiff}{Generic Function for the Computation of Inefficiency Differences}{getIneffDiff}
+\aliasA{getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType-method}{getIneffDiff}{getIneffDiff,numeric,L2ParamFamily,UncondNeighborhood,asMSE,BiasType.Rdash.method}
+\aliasA{getIneffDiff-methods}{getIneffDiff}{getIneffDiff.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of inefficiency differencies.
+This function is rarely called directly. It is used to compute
+the radius minimax IC and the least favorable radius.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getIneffDiff(radius, L2Fam, neighbor, risk, biastype, ...)
+
+## S4 method for signature 'numeric, L2ParamFamily,
+## UncondNeighborhood, asMSE, BiasType':
+getIneffDiff(
+ radius, L2Fam, neighbor, risk, biastype = symmetricBias(), loRad, upRad,
+ loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{radius}] neighborhood radius.
+\item[\code{L2Fam}] L2-differentiable family of probability measures.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{...}] additional parameters
+\item[\code{loRad}] the lower end point of the interval to be searched.
+\item[\code{upRad}] the upper end point of the interval to be searched.
+\item[\code{loRisk}] the risk at the lower end point of the interval.
+\item[\code{upRisk}] the risk at the upper end point of the interval.
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{upper.b}] upper bound for the optimal clipping bound.
+\item[\code{MaxIter}] the maximum number of iterations
+\item[\code{eps}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The inefficieny difference between the left and
+the right margin of a given radius interval is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[radius = "numeric", L2Fam = "L2ParamFamily",
+neighbor = "UncondNeighborhood", risk = "asMSE", biastype = "BiasType":] computes difference of asymptotic MSE--inefficiency for
+the boundaries of a given radius interval.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+\url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{radiusMinimaxIC}{radiusMinimaxIC}}, \code{\LinkA{leastFavorableRadius}{leastFavorableRadius}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getInfCent.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getInfCent.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getInfCent.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,94 @@
+\HeaderA{getInfCent}{Generic Function for the Computation of the Optimal Centering Constant/Lower Clipping Bound}{getInfCent}
+\aliasA{getInfCent,RealRandVariable,ContNeighborhood,BiasType-method}{getInfCent}{getInfCent,RealRandVariable,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}{getInfCent}{getInfCent,UnivariateDistribution,ContNeighborhood,asymmetricBias.Rdash.method}
+\aliasA{getInfCent,UnivariateDistribution,ContNeighborhood,BiasType-method}{getInfCent}{getInfCent,UnivariateDistribution,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias-method}{getInfCent}{getInfCent,UnivariateDistribution,ContNeighborhood,onesidedBias.Rdash.method}
+\aliasA{getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}{getInfCent}{getInfCent,UnivariateDistribution,TotalVarNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfCent-methods}{getInfCent}{getInfCent.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the optimal centering constant
+(contamination neighborhoods) respectively, of the optimal lower clipping
+bound (total variation neighborhood).
+This function is rarely called directly. It is used to
+compute optimally robust ICs.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getInfCent(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+getInfCent(L2deriv,
+ neighbor, biastype = symmetricBias(), z.comp, stand, cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, onesidedBias':
+getInfCent(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, tol.z, symm, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+getInfCent(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, tol.z, symm, trafo)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability measures.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{biastype}] object of class \code{"BiasType"}
+\item[\code{...}] additional parameters.
+\item[\code{clip}] optimal clipping bound.
+\item[\code{cent}] optimal centering constant.
+\item[\code{stand}] standardizing matrix.
+\item[\code{tol.z}] the desired accuracy (convergence tolerance).
+\item[\code{symm}] logical: indicating symmetry of \code{L2deriv}.
+\item[\code{trafo}] matrix: transformation of the parameter.
+\item[\code{z.comp}] logical vector: indication which components of the
+centering constant have to be computed.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The optimal centering constant is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "BiasType"] computation of optimal centering constant for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood", biastype = "BiasType"] computation of optimal lower clipping bound for symmetric bias.
+
+\item[L2deriv = "RealRandVariable", neighbor = "ContNeighborhood", biastype = "BiasType"] computation of optimal centering constant for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "onesidedBias"] computation of optimal centering constant for onesided bias.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood", biastype = "asymmetricBias"] computation of optimal centering constant for asymmetric bias.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{ContIC-class}{ContIC.Rdash.class}}, \code{\LinkA{TotalVarIC-class}{TotalVarIC.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getInfClip.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getInfClip.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getInfClip.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,95 @@
+\HeaderA{getInfClip}{Generic Function for the Computation of the Optimal Clipping Bound}{getInfClip}
+\aliasA{getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood-method}{getInfClip}{getInfClip,numeric,EuclRandVariable,asMSE,ContNeighborhood.Rdash.method}
+\aliasA{getInfClip,numeric,UnivariateDistribution,asMSE,ContNeighborhood-method}{getInfClip}{getInfClip,numeric,UnivariateDistribution,asMSE,ContNeighborhood.Rdash.method}
+\aliasA{getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood-method}{getInfClip}{getInfClip,numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood.Rdash.method}
+\aliasA{getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood-method}{getInfClip}{getInfClip,numeric,UnivariateDistribution,asSemivar,ContNeighborhood.Rdash.method}
+\aliasA{getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method}{getInfClip}{getInfClip,numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood.Rdash.method}
+\aliasA{getInfClip-methods}{getInfClip}{getInfClip.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the optimal clipping bound
+in case of infinitesimal robust models. This function is rarely called
+directly. It is used to compute optimally robust ICs.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getInfClip(clip, L2deriv, risk, neighbor, ...)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asMSE, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asMSE, TotalVarNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric, EuclRandVariable,
+## asMSE, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, Distr, stand, biastype, cent, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asUnOvShoot,
+## UncondNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+
+## S4 method for signature 'numeric,
+## UnivariateDistribution, asSemivar, ContNeighborhood':
+getInfClip(clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{clip}] positive real: clipping bound
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability measures.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{...}] additional parameters.
+\item[\code{biastype}] object of class \code{"BiasType"}
+\item[\code{cent}] optimal centering constant.
+\item[\code{stand}] standardizing matrix.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{symm}] logical: indicating symmetry of \code{L2deriv}.
+\item[\code{trafo}] matrix: transformation of the parameter.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The optimal clipping bound is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asMSE", neighbor = "ContNeighborhood"] optimal clipping bound for asymtotic mean square error.
+
+
+\item[clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asMSE", neighbor = "TotalVarNeighborhood"] optimal clipping bound for asymtotic mean square error.
+
+\item[clip = "numeric", L2deriv = "EuclRandVariable",
+risk = "asMSE", neighbor = "ContNeighborhood"] optimal clipping bound for asymtotic mean square error.
+
+\item[clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asUnOvShoot", neighbor = "UncondNeighborhood"] optimal clipping bound for asymtotic under-/overshoot risk.
+
+\item[clip = "numeric", L2deriv = "UnivariateDistribution",
+risk = "asSemivar", neighbor = "ContNeighborhood"] optimal clipping bound for asymtotic semivariance.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{ContIC-class}{ContIC.Rdash.class}}, \code{\LinkA{TotalVarIC-class}{TotalVarIC.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getInfGamma.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getInfGamma.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getInfGamma.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,117 @@
+\HeaderA{getInfGamma}{Generic Function for the Computation of the Optimal Clipping Bound}{getInfGamma}
+\aliasA{getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType-method}{getInfGamma}{getInfGamma,RealRandVariable,asMSE,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType-method}{getInfGamma}{getInfGamma,UnivariateDistribution,asGRisk,TotalVarNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias-method}{getInfGamma}{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,asymmetricBias.Rdash.method}
+\aliasA{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType-method}{getInfGamma}{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias-method}{getInfGamma}{getInfGamma,UnivariateDistribution,asMSE,ContNeighborhood,onesidedBias.Rdash.method}
+\aliasA{getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType-method}{getInfGamma}{getInfGamma,UnivariateDistribution,asUnOvShoot,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfGamma-methods}{getInfGamma}{getInfGamma.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the optimal clipping bound.
+This function is rarely called directly. It is called by \code{getInfClip}
+to compute optimally robust ICs.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getInfGamma(L2deriv, risk, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## asGRisk, TotalVarNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'RealRandVariable, asMSE,
+## ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), Distr, stand, cent, clip)
+
+## S4 method for signature 'UnivariateDistribution,
+## asUnOvShoot, ContNeighborhood, BiasType':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = symmetricBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, onesidedBias':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = positiveBias(), cent, clip)
+
+## S4 method for signature 'UnivariateDistribution, asMSE,
+## ContNeighborhood, asymmetricBias':
+getInfGamma(L2deriv,
+ risk, neighbor, biastype = asymmetricBias(), cent, clip)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability measures.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{biastype}] object of class \code{"BiasType"}
+\item[\code{...}] additional parameters
+\item[\code{cent}] optimal centering constant.
+\item[\code{clip}] optimal clipping bound.
+\item[\code{stand}] standardizing matrix.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\end{ldescription}
+\end{Arguments}
+\begin{Details}\relax
+The function is used in case of asymptotic G-risks; confer
+Ruckdeschel and Rieder (2004).
+\end{Details}
+\begin{Section}{Methods}
+\describe{
+\item[L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "BiasType"] used by \code{getInfClip} for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asGRisk",
+neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"] used by \code{getInfClip} for symmetric bias.
+
+\item[L2deriv = "RealRandVariable", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "BiasType"] used by \code{getInfClip} for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",
+neighbor = "ContNeighborhood",
+biastype = "BiasType"] used by \code{getInfClip} for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "onesidedBias"] used by \code{getInfClip} for onesided bias.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asMSE",
+neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"] used by \code{getInfClip} for asymmetric bias.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics \& Decisions \emph{22}, 201-223.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{asGRisk-class}{asGRisk.Rdash.class}}, \code{\LinkA{asMSE-class}{asMSE.Rdash.class}},
+\code{\LinkA{asUnOvShoot-class}{asUnOvShoot.Rdash.class}}, \code{\LinkA{ContIC-class}{ContIC.Rdash.class}},
+\code{\LinkA{TotalVarIC-class}{TotalVarIC.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getInfRobIC.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getInfRobIC.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getInfRobIC.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,164 @@
+\HeaderA{getInfRobIC}{Generic Function for the Computation of Optimally Robust ICs}{getInfRobIC}
+\aliasA{getInfRobIC,RealRandVariable,asBias,ContNeighborhood-method}{getInfRobIC}{getInfRobIC,RealRandVariable,asBias,ContNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,RealRandVariable,asCov,ContNeighborhood-method}{getInfRobIC}{getInfRobIC,RealRandVariable,asCov,ContNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood-method}{getInfRobIC}{getInfRobIC,RealRandVariable,asGRisk,ContNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,RealRandVariable,asHampel,ContNeighborhood-method}{getInfRobIC}{getInfRobIC,RealRandVariable,asHampel,ContNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood-method}{getInfRobIC}{getInfRobIC,UnivariateDistribution,asBias,UncondNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood-method}{getInfRobIC}{getInfRobIC,UnivariateDistribution,asCov,ContNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood-method}{getInfRobIC}{getInfRobIC,UnivariateDistribution,asCov,TotalVarNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood-method}{getInfRobIC}{getInfRobIC,UnivariateDistribution,asGRisk,UncondNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood-method}{getInfRobIC}{getInfRobIC,UnivariateDistribution,asHampel,UncondNeighborhood.Rdash.method}
+\aliasA{getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood-method}{getInfRobIC}{getInfRobIC,UnivariateDistribution,asUnOvShoot,UncondNeighborhood.Rdash.method}
+\aliasA{getInfRobIC-methods}{getInfRobIC}{getInfRobIC.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of optimally robust ICs
+in case of infinitesimal robust models. This function is
+rarely called directly.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getInfRobIC(L2deriv, risk, neighbor, ...)
+
+## S4 method for signature 'UnivariateDistribution, asCov,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
+
+## S4 method for signature 'UnivariateDistribution, asCov,
+## TotalVarNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)
+
+## S4 method for signature 'RealRandVariable, asCov,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo)
+
+## S4 method for signature 'UnivariateDistribution, asBias,
+## UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable, asBias,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## asHampel, UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable, asHampel,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## asGRisk, UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable, asGRisk,
+## ContNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## asUnOvShoot, UncondNeighborhood':
+getInfRobIC(L2deriv, risk, neighbor, biastype, symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability measures.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{...}] additional parameters.
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{symm}] logical: indicating symmetry of \code{L2deriv}.
+\item[\code{DistrSymm}] object of class \code{"DistributionSymmetry"}.
+\item[\code{L2derivSymm}] object of class \code{"FunSymmList"}.
+\item[\code{L2derivDistrSymm}] object of class \code{"DistrSymmList"}.
+\item[\code{Finfo}] Fisher information matrix.
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{trafo}] matrix: transformation of the parameter.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations.
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The optimally robust IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2deriv = "UnivariateDistribution", risk = "asCov",
+neighbor = "ContNeighborhood"] computes the classical optimal influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asCov",
+neighbor = "TotalVarNeighborhood"] computes the classical optimal influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "RealRandVariable", risk = "asCov",
+neighbor = "ContNeighborhood"] computes the classical optimal influence curve for L2 differentiable
+parametric families with unknown \eqn{k}{}-dimensional parameter
+(\eqn{k > 1}{}) where the underlying distribution is univariate.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asBias",
+neighbor = "UncondNeighborhood"] computes the bias optimal influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "RealRandVariable", risk = "asBias",
+neighbor = "ContNeighborhood"] computes the bias optimal influence curve for L2 differentiable
+parametric families with unknown \eqn{k}{}-dimensional parameter
+(\eqn{k > 1}{}) where the underlying distribution is univariate.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asHampel",
+neighbor = "UncondNeighborhood"] computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "RealRandVariable", risk = "asHampel",
+neighbor = "ContNeighborhood"] computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown \eqn{k}{}-dimensional parameter
+(\eqn{k > 1}{}) where the underlying distribution is univariate.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asGRisk",
+neighbor = "UncondNeighborhood"] computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "RealRandVariable", risk = "asGRisk",
+neighbor = "ContNeighborhood"] computes the optimally robust influence curve for L2 differentiable
+parametric families with unknown \eqn{k}{}-dimensional parameter
+(\eqn{k > 1}{}) where the underlying distribution is univariate.
+
+\item[L2deriv = "UnivariateDistribution", risk = "asUnOvShoot",
+neighbor = "UncondNeighborhood"] computes the optimally robust influence curve for one-dimensional
+L2 differentiable parametric families and
+asymptotic under-/overshoot risk.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106-115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for
+General Loss Functions. Statistics \& Decisions \bold{22}: 201-223.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{InfRobModel-class}{InfRobModel.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getInfStand.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getInfStand.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getInfStand.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,96 @@
+\HeaderA{getInfStand}{Generic Function for the Computation of the Standardizing Matrix}{getInfStand}
+\aliasA{getInfStand,RealRandVariable,ContNeighborhood,BiasType-method}{getInfStand}{getInfStand,RealRandVariable,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}{getInfStand}{getInfStand,UnivariateDistribution,ContNeighborhood,asymmetricBias.Rdash.method}
+\aliasA{getInfStand,UnivariateDistribution,ContNeighborhood,BiasType-method}{getInfStand}{getInfStand,UnivariateDistribution,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias-method}{getInfStand}{getInfStand,UnivariateDistribution,ContNeighborhood,onesidedBias.Rdash.method}
+\aliasA{getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}{getInfStand}{getInfStand,UnivariateDistribution,TotalVarNeighborhood,BiasType.Rdash.method}
+\aliasA{getInfStand-methods}{getInfStand}{getInfStand.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the standardizing matrix which
+takes care of the Fisher consistency of the corresponding IC. This function
+is rarely called directly. It is used to compute optimally robust ICs.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getInfStand(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), clip, cent, trafo)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = symmetricBias(), Distr, A.comp, stand, clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = positiveBias(), clip, cent, trafo)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+getInfStand(L2deriv,
+ neighbor, biastype = asymmetricBias(), clip, cent, trafo)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability measures.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}
+\item[\code{biastype}] object of class \code{"BiasType"}
+\item[\code{...}] additional parameters
+\item[\code{clip}] optimal clipping bound.
+\item[\code{cent}] optimal centering constant.
+\item[\code{stand}] standardizing matrix.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{trafo}] matrix: transformation of the parameter.
+\item[\code{A.comp}] matrix: indication which components of the standardizing
+matrix have to be computed.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The standardizing matrix is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "BiasType"] computes standardizing matrix for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"] computes standardizing matrix for symmetric bias.
+
+\item[L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+biastype = "BiasType"] computes standardizing matrix for symmetric bias.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "onesidedBias"] computes standardizing matrix for onesided bias.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"] computes standardizing matrix for asymmetric bias.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{ContIC-class}{ContIC.Rdash.class}}, \code{\LinkA{TotalVarIC-class}{TotalVarIC.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getL1normL2deriv.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getL1normL2deriv.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getL1normL2deriv.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,40 @@
+\HeaderA{getL1normL2deriv}{Calculation of L1 norm of L2derivative}{getL1normL2deriv}
+\aliasA{getL1normL2deriv,RealRandVariable-method}{getL1normL2deriv}{getL1normL2deriv,RealRandVariable.Rdash.method}
+\aliasA{getL1normL2deriv,UnivariateDistribution-method}{getL1normL2deriv}{getL1normL2deriv,UnivariateDistribution.Rdash.method}
+\aliasA{getL1normL2deriv-methods}{getL1normL2deriv}{getL1normL2deriv.Rdash.methods}
+\begin{Description}\relax
+Methods to calculate the L1 norm of the L2derivative in a smooth parametric model.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}getL1normL2deriv(L2deriv, ...)
+## S4 method for signature 'UnivariateDistribution':
+getL1normL2deriv(L2deriv,
+ cent, ...)
+
+## S4 method for signature 'UnivariateDistribution':
+getL1normL2deriv(L2deriv,
+ cent, stand, Distr, ...)
+
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2deriv}] L2derivative of the model
+\item[\code{cent}] centering Lagrange Multiplier
+\item[\code{stand}] standardizing Lagrange Multiplier
+\item[\code{Distr}] distribution of the L2derivative
+\item[\code{...}] further arguments (not used at the moment)
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+L1 norm of the L2derivative
+\end{Value}
+\begin{Author}\relax
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{Examples}
+\begin{ExampleCode}
+##
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getL2normL2deriv.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getL2normL2deriv.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getL2normL2deriv.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,26 @@
+\HeaderA{getL2normL2deriv}{Calculation of L2 norm of L2derivative}{getL2normL2deriv}
+\begin{Description}\relax
+Function to calculate the L2 norm of the L2derivative in a smooth parametric model.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}getL2normL2deriv(aFinfo, cent, ...)\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{aFinfo}] trace of the Fisher information
+\item[\code{cent}] centering
+\item[\code{...}] further arguments (not used at the moment)
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+L2 norm of the L2derivative
+\end{Value}
+\begin{Author}\relax
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{Examples}
+\begin{ExampleCode}
+##
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/getRiskIC.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/getRiskIC.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/getRiskIC.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,139 @@
+\HeaderA{getRiskIC}{Generic function for the computation of a risk for an IC}{getRiskIC}
+\aliasA{getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily-method}{getRiskIC}{getRiskIC,IC,asBias,UncondNeighborhood,L2ParamFamily.Rdash.method}
+\aliasA{getRiskIC,IC,asBias,UncondNeighborhood,missing-method}{getRiskIC}{getRiskIC,IC,asBias,UncondNeighborhood,missing.Rdash.method}
+\aliasA{getRiskIC,IC,asCov,missing,L2ParamFamily-method}{getRiskIC}{getRiskIC,IC,asCov,missing,L2ParamFamily.Rdash.method}
+\aliasA{getRiskIC,IC,asCov,missing,missing-method}{getRiskIC}{getRiskIC,IC,asCov,missing,missing.Rdash.method}
+\aliasA{getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily-method}{getRiskIC}{getRiskIC,IC,asMSE,UncondNeighborhood,L2ParamFamily.Rdash.method}
+\aliasA{getRiskIC,IC,asMSE,UncondNeighborhood,missing-method}{getRiskIC}{getRiskIC,IC,asMSE,UncondNeighborhood,missing.Rdash.method}
+\aliasA{getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing-method}{getRiskIC}{getRiskIC,IC,fiUnOvShoot,ContNeighborhood,missing.Rdash.method}
+\aliasA{getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing-method}{getRiskIC}{getRiskIC,IC,fiUnOvShoot,TotalVarNeighborhood,missing.Rdash.method}
+\aliasA{getRiskIC,IC,trAsCov,missing,L2ParamFamily-method}{getRiskIC}{getRiskIC,IC,trAsCov,missing,L2ParamFamily.Rdash.method}
+\aliasA{getRiskIC,IC,trAsCov,missing,missing-method}{getRiskIC}{getRiskIC,IC,trAsCov,missing,missing.Rdash.method}
+\aliasA{getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing-method}{getRiskIC}{getRiskIC,TotalVarIC,asUnOvShoot,UncondNeighborhood,missing.Rdash.method}
+\aliasA{getRiskIC-methods}{getRiskIC}{getRiskIC.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of a risk for an IC.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+getRiskIC(IC, risk, neighbor, L2Fam, ...)
+
+## S4 method for signature 'IC, asCov, missing, missing':
+getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asCov, missing,
+## L2ParamFamily':
+getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, trAsCov, missing, missing':
+getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, trAsCov, missing,
+## L2ParamFamily':
+getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## missing':
+getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asBias, UncondNeighborhood,
+## L2ParamFamily':
+getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+## missing':
+getRiskIC(IC, risk, neighbor, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'IC, asMSE, UncondNeighborhood,
+## L2ParamFamily':
+getRiskIC(IC, risk, neighbor, L2Fam, biastype = symmetricBias(), tol = .Machine$double.eps^0.25)
+
+## S4 method for signature 'TotalVarIC, asUnOvShoot,
+## UncondNeighborhood, missing':
+getRiskIC(IC, risk, neighbor)
+
+## S4 method for signature 'IC, fiUnOvShoot,
+## ContNeighborhood, missing':
+getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+
+## S4 method for signature 'IC, fiUnOvShoot,
+## TotalVarNeighborhood, missing':
+getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{IC}] object of class \code{"InfluenceCurve"}
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{L2Fam}] object of class \code{"L2ParamFamily"}.
+\item[\code{...}] additional parameters
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{sampleSize}] integer: sample size.
+\item[\code{Algo}] "A" or "B".
+\item[\code{cont}] "left" or "right".
+\end{ldescription}
+\end{Arguments}
+\begin{Details}\relax
+To make sure that the results are valid, it is recommended
+to include an additional check of the IC properties of \code{IC}
+using \code{checkIC}.
+\end{Details}
+\begin{Value}
+The risk of an IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "missing"] asymptotic covariance of \code{IC}.
+
+\item[IC = "IC", risk = "asCov", neighbor = "missing", L2Fam = "L2ParamFamily"] asymptotic covariance of \code{IC} under \code{L2Fam}.
+
+\item[IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "missing"] asymptotic covariance of \code{IC}.
+
+\item[IC = "IC", risk = "trAsCov", neighbor = "missing", L2Fam = "L2ParamFamily"] asymptotic covariance of \code{IC} under \code{L2Fam}.
+
+\item[IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "missing"] asymptotic bias of \code{IC} under convex contaminations.
+
+\item[IC = "IC", risk = "asBias", neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily"] asymptotic bias of \code{IC} under convex contaminations and \code{L2Fam}.
+
+\item[IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "missing"] asymptotic bias of \code{IC} in case of total variation neighborhoods.
+
+\item[IC = "IC", risk = "asBias", neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily"] asymptotic bias of \code{IC} under \code{L2Fam} in case of total variation
+neighborhoods.
+
+\item[IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "missing"] asymptotic mean square error of \code{IC}.
+
+\item[IC = "IC", risk = "asMSE", neighbor = "UncondNeighborhood", L2Fam = "L2ParamFamily"] asymptotic mean square error of \code{IC} under \code{L2Fam}.
+
+\item[IC = "TotalVarIC", risk = "asUnOvShoot", neighbor = "UncondNeighborhood", L2Fam = "missing"] asymptotic under-/overshoot risk of \code{IC}.
+
+\item[IC = "IC", risk = "fiUnOvShoot", neighbor = "ContNeighborhood", L2Fam = "missing"] finite-sample under-/overshoot risk of \code{IC}.
+
+\item[IC = "IC", risk = "fiUnOvShoot", neighbor = "TotalVarNeighborhood", L2Fam = "missing"] finite-sample under-/overshoot risk of \code{IC}.
+}
+\end{Section}
+\begin{Note}\relax
+This generic function is still under construction.
+\end{Note}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. \bold{10}:269--278.
+
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+
+Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk
+of M-estimators on Neighborhoods.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{getRiskIC-methods}{getRiskIC.Rdash.methods}}, \code{\LinkA{InfRobModel-class}{InfRobModel.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/leastFavorableRadius.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/leastFavorableRadius.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/leastFavorableRadius.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,77 @@
+\HeaderA{leastFavorableRadius}{Generic Function for the Computation of Least Favorable Radii}{leastFavorableRadius}
+\aliasA{leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method}{leastFavorableRadius}{leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk.Rdash.method}
+\aliasA{leastFavorableRadius-methods}{leastFavorableRadius}{leastFavorableRadius.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of least favorable radii.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+leastFavorableRadius(L2Fam, neighbor, risk, ...)
+
+## S4 method for signature 'L2ParamFamily,
+## UncondNeighborhood, asGRisk':
+leastFavorableRadius(
+ L2Fam, neighbor, risk, biastype = symmetricBias(), rho, upRad = 1,
+ z.start = NULL, A.start = NULL, upper = 100, maxiter = 100,
+ tol = .Machine$double.eps^0.4, warn = FALSE)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2Fam}] L2-differentiable family of probability measures.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{...}] additional parameters
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{upRad}] the upper end point of the radius interval to be searched.
+\item[\code{rho}] The considered radius interval is: \eqn{[r \rho, r/\rho]}{[r*rho, r/rho]}
+with \eqn{\rho\in(0,1)}{0 < rho < 1}.
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The least favorable radius and the corresponding inefficiency
+are computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood",
+risk = "asGRisk"] computation of the least favorable radius.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+the Radius. Statistical Methods and Applications \emph{17}(1) 13-40.
+
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+\url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{radiusMinimaxIC}{radiusMinimaxIC}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+N <- NormLocationFamily(mean=0, sd=1)
+leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5)
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/locMEstimator.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/locMEstimator.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/locMEstimator.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,49 @@
+\HeaderA{locMEstimator}{Generic function for the computation of location M estimators}{locMEstimator}
+\aliasA{locMEstimator,numeric,InfluenceCurve-method}{locMEstimator}{locMEstimator,numeric,InfluenceCurve.Rdash.method}
+\aliasA{locMEstimator-methods}{locMEstimator}{locMEstimator.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of location M estimators.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+locMEstimator(x, IC, ...)
+
+## S4 method for signature 'numeric, InfluenceCurve':
+locMEstimator(x, IC, eps = .Machine$double.eps^0.5)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{x}] sample
+\item[\code{IC}] object of class \code{"InfluenceCurve"}
+\item[\code{...}] additional parameters
+\item[\code{eps}] the desired accuracy (convergence tolerance).
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+Returns a list with component
+\begin{ldescription}
+\item[\code{loc}] M estimator of location
+\end{ldescription}
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[x = "numeric", IC = "InfluenceCurve"] univariate location.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1964) Robust estimation of a location parameter.
+Ann. Math. Stat. \bold{35}: 73--101.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{InfluenceCurve-class}{InfluenceCurve.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/lowerCaseRadius.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/lowerCaseRadius.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/lowerCaseRadius.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,57 @@
+\HeaderA{lowerCaseRadius}{Computation of the lower case radius}{lowerCaseRadius}
+\aliasA{lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method}{lowerCaseRadius}{lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType.Rdash.method}
+\aliasA{lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-method}{lowerCaseRadius}{lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType.Rdash.method}
+\aliasA{lowerCaseRadius-methods}{lowerCaseRadius}{lowerCaseRadius.Rdash.methods}
+\begin{Description}\relax
+The lower case radius is computed; confer Subsection 2.1.2
+in Kohl (2005) and formula (4.5) in Ruckdeschel (2005).
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+lowerCaseRadius(L2Fam, neighbor, risk, biastype, ...)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2Fam}] L2 differentiable parametric family
+\item[\code{neighbor}] object of class \code{"Neighborhood"}
+\item[\code{risk}] object of class \code{"RiskType"}
+\item[\code{biastype}] object of class \code{"BiasType"}
+\item[\code{...}] additional parameters
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+lower case radius
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2Fam = "L2ParamFamily", neighbor = "ContNeighborhood", risk = "asMSE",
+biastype = "BiasType"] lower case radius for risk \code{"asMSE"} in case of \code{"ContNeighborhood"}
+for symmetric bias.
+
+\item[L2Fam = "L2ParamFamily", neighbor = "TotalVarNeighborhood", risk = "asMSE",
+biastype = "BiasType"] lower case radius for risk \code{"asMSE"} in case of \code{"TotalVarNeighborhood"};
+(argument biastype is just for signature reasons).
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{L2ParamFamily-class}{L2ParamFamily.Rdash.class}}, \code{\LinkA{Neighborhood-class}{Neighborhood.Rdash.class}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+lowerCaseRadius(BinomFamily(size = 10), ContNeighborhood(), asMSE())
+lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/minmaxBias.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/minmaxBias.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/minmaxBias.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,102 @@
+\HeaderA{minmaxBias}{Generic Function for the Computation of Bias-Optimally Robust ICs}{minmaxBias}
+\aliasA{minmaxBias,RealRandVariable,ContNeighborhood,BiasType-method}{minmaxBias}{minmaxBias,RealRandVariable,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias-method}{minmaxBias}{minmaxBias,UnivariateDistribution,ContNeighborhood,asymmetricBias.Rdash.method}
+\aliasA{minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType-method}{minmaxBias}{minmaxBias,UnivariateDistribution,ContNeighborhood,BiasType.Rdash.method}
+\aliasA{minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType-method}{minmaxBias}{minmaxBias,UnivariateDistribution,TotalVarNeighborhood,BiasType.Rdash.method}
+\aliasA{minmaxBias-methods}{minmaxBias}{minmaxBias.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of bias-optimally robust ICs
+in case of infinitesimal robust models. This function is
+rarely called directly.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+minmaxBias(L2deriv, neighbor, biastype, ...)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## ContNeighborhood, asymmetricBias':
+minmaxBias(L2deriv, neighbor, biastype = asymmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'UnivariateDistribution,
+## TotalVarNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), symm, Finfo, trafo,
+ upper, maxiter, tol, warn)
+
+## S4 method for signature 'RealRandVariable,
+## ContNeighborhood, BiasType':
+minmaxBias(L2deriv, neighbor, biastype = symmetricBias(), Distr, DistrSymm, L2derivSymm,
+ L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)
+
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2deriv}] L2-derivative of some L2-differentiable family
+of probability measures.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{...}] additional parameters.
+\item[\code{Distr}] object of class \code{"Distribution"}.
+\item[\code{symm}] logical: indicating symmetry of \code{L2deriv}.
+\item[\code{DistrSymm}] object of class \code{"DistributionSymmetry"}.
+\item[\code{L2derivSymm}] object of class \code{"FunSymmList"}.
+\item[\code{L2derivDistrSymm}] object of class \code{"DistrSymmList"}.
+\item[\code{Finfo}] Fisher information matrix.
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{trafo}] matrix: transformation of the parameter.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations.
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The bias-optimally robust IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "BiasType"] computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "ContNeighborhood",
+biastype = "asymmetricBias"] computes the bias optimal influence curve for asymmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "UnivariateDistribution", neighbor = "TotalVarNeighborhood",
+biastype = "BiasType"] computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown one-dimensional parameter.
+
+\item[L2deriv = "RealRandVariable", neighbor = "ContNeighborhood",
+biastype = "BiasType"] computes the bias optimal influence curve for symmetric bias for L2 differentiable
+parametric families with unknown \eqn{k}{}-dimensional parameter
+(\eqn{k > 1}{}) where the underlying distribution is univariate.
+
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves.
+Mathematical Methods in Statistics \emph{14}(1), 105-131.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{InfRobModel-class}{InfRobModel.Rdash.class}}
+\end{SeeAlso}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/optIC.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/optIC.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/optIC.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,104 @@
+\HeaderA{optIC}{Generic function for the computation of optimally robust ICs}{optIC}
+\aliasA{optIC,FixRobModel,fiUnOvShoot-method}{optIC}{optIC,FixRobModel,fiUnOvShoot.Rdash.method}
+\aliasA{optIC,InfRobModel,asRisk-method}{optIC}{optIC,InfRobModel,asRisk.Rdash.method}
+\aliasA{optIC,InfRobModel,asUnOvShoot-method}{optIC}{optIC,InfRobModel,asUnOvShoot.Rdash.method}
+\aliasA{optIC,L2ParamFamily,asCov-method}{optIC}{optIC,L2ParamFamily,asCov.Rdash.method}
+\aliasA{optIC-methods}{optIC}{optIC.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of optimally robust ICs.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+optIC(model, risk, ...)
+
+## S4 method for signature 'L2ParamFamily, asCov':
+optIC(model, risk)
+
+## S4 method for signature 'InfRobModel, asRisk':
+optIC(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
+## S4 method for signature 'InfRobModel, asUnOvShoot':
+optIC(model, risk, biastype = symmetricBias(),
+ upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE)
+
+## S4 method for signature 'FixRobModel, fiUnOvShoot':
+optIC(model, risk, sampleSize, upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{model}] probability model.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{...}] additional parameters.
+\item[\code{biastype}] object of class \code{"BiasType"}
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations.
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\item[\code{sampleSize}] integer: sample size.
+\item[\code{Algo}] "A" or "B".
+\item[\code{cont}] "left" or "right".
+\end{ldescription}
+\end{Arguments}
+\begin{Details}\relax
+In case of the finite-sample risk \code{"fiUnOvShoot"} one can choose
+between two algorithms for the computation of this risk where the least favorable
+contamination is assumed to be left or right of some bound. For more details
+we refer to Section 11.3 of Kohl (2005).
+\end{Details}
+\begin{Value}
+Some optimally robust IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[model = "L2ParamFamily", risk = "asCov"] computes
+classical optimal influence curve for L2 differentiable
+parametric families.
+
+\item[model = "InfRobModel", risk = "asRisk"] computes optimally robust influence curve for
+robust models with infinitesimal neighborhoods and
+various asymptotic risks.
+
+\item[model = "InfRobModel", risk = "asUnOvShoot"] computes optimally robust influence curve for
+robust models with infinitesimal neighborhoods and
+asymptotic under-/overshoot risk.
+
+\item[model = "FixRobModel", risk = "fiUnOvShoot"] computes optimally robust influence curve for
+robust models with fixed neighborhoods and
+finite-sample under-/overshoot risk.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. \bold{10}:269--278.
+
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{InfluenceCurve-class}{InfluenceCurve.Rdash.class}}, \code{\LinkA{RiskType-class}{RiskType.Rdash.class}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+B <- BinomFamily(size = 25, prob = 0.25)
+
+## classical optimal IC
+IC0 <- optIC(model = B, risk = asCov())
+plot(IC0) # plot IC
+checkIC(IC0, B)
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/optRisk.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/optRisk.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/optRisk.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,86 @@
+\HeaderA{optRisk}{Generic function for the computation of the minimal risk}{optRisk}
+\aliasA{optRisk,FixRobModel,fiUnOvShoot-method}{optRisk}{optRisk,FixRobModel,fiUnOvShoot.Rdash.method}
+\aliasA{optRisk,InfRobModel,asRisk-method}{optRisk}{optRisk,InfRobModel,asRisk.Rdash.method}
+\aliasA{optRisk,L2ParamFamily,asCov-method}{optRisk}{optRisk,L2ParamFamily,asCov.Rdash.method}
+\aliasA{optRisk-methods}{optRisk}{optRisk.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the optimal (i.e., minimal)
+risk for a probability model.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+optRisk(model, risk, ...)
+
+## S4 method for signature 'L2ParamFamily, asCov':
+optRisk(model, risk)
+
+## S4 method for signature 'InfRobModel, asRisk':
+optRisk(model, risk, biastype = symmetricBias(),
+ z.start = NULL, A.start = NULL, upper = 1e4,
+ maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
+
+## S4 method for signature 'FixRobModel, fiUnOvShoot':
+optRisk(model, risk, sampleSize, upper = 1e4, maxiter = 50,
+ tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{model}] probability model
+\item[\code{risk}] object of class \code{RiskType}
+\item[\code{...}] additional parameters
+\item[\code{biastype}] object of class \code{BiasType}
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\item[\code{sampleSize}] integer: sample size.
+\item[\code{Algo}] "A" or "B".
+\item[\code{cont}] "left" or "right".
+\end{ldescription}
+\end{Arguments}
+\begin{Details}\relax
+In case of the finite-sample risk \code{"fiUnOvShoot"} one can choose
+between two algorithms for the computation of this risk where the least favorable
+contamination is assumed to be left or right of some bound. For more details
+we refer to Section 11.3 of Kohl (2005).
+\end{Details}
+\begin{Value}
+The minimal risk is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[model = "L2ParamFamily", risk = "asCov"] asymptotic covariance of L2 differentiable parameteric
+family.
+
+\item[model = "InfRobModel", risk = "asRisk"] asymptotic risk of a infinitesimal robust model.
+
+\item[model = "FixRobModel", risk = "fiUnOvShoot"] finite-sample under-/overshoot risk of a robust model
+with fixed neighborhood.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor.
+Verw. Geb. \bold{10}:269--278.
+
+Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. \bold{8}: 106--115.
+
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{RiskType-class}{RiskType.Rdash.class}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+optRisk(model = NormLocationScaleFamily(), risk = asCov())
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/radiusMinimaxIC.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/radiusMinimaxIC.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/radiusMinimaxIC.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,68 @@
+\HeaderA{radiusMinimaxIC}{Generic function for the computation of the radius minimax IC}{radiusMinimaxIC}
+\aliasA{radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method}{radiusMinimaxIC}{radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk.Rdash.method}
+\aliasA{radiusMinimaxIC-methods}{radiusMinimaxIC}{radiusMinimaxIC.Rdash.methods}
+\begin{Description}\relax
+Generic function for the computation of the radius minimax IC.
+\end{Description}
+\begin{Usage}
+\begin{verbatim}
+radiusMinimaxIC(L2Fam, neighbor, risk, ...)
+
+## S4 method for signature 'L2ParamFamily,
+## UncondNeighborhood, asGRisk':
+radiusMinimaxIC(
+ L2Fam, neighbor, risk, biastype = symmetricBias(),
+ loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5,
+ maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)
+\end{verbatim}
+\end{Usage}
+\begin{Arguments}
+\begin{ldescription}
+\item[\code{L2Fam}] L2-differentiable family of probability measures.
+\item[\code{neighbor}] object of class \code{"Neighborhood"}.
+\item[\code{risk}] object of class \code{"RiskType"}.
+\item[\code{...}] additional parameters.
+\item[\code{biastype}] object of class \code{"BiasType"}.
+\item[\code{loRad}] the lower end point of the interval to be searched.
+\item[\code{upRad}] the upper end point of the interval to be searched.
+\item[\code{z.start}] initial value for the centering constant.
+\item[\code{A.start}] initial value for the standardizing matrix.
+\item[\code{upper}] upper bound for the optimal clipping bound.
+\item[\code{maxiter}] the maximum number of iterations
+\item[\code{tol}] the desired accuracy (convergence tolerance).
+\item[\code{warn}] logical: print warnings.
+\end{ldescription}
+\end{Arguments}
+\begin{Value}
+The radius minimax IC is computed.
+\end{Value}
+\begin{Section}{Methods}
+\describe{
+\item[L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asGRisk":] computation of the radius minimax IC for an L2 differentiable parametric family.
+}
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de},
+Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+\url{www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf}
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{radiusMinimaxIC}{radiusMinimaxIC}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+N <- NormLocationFamily(mean=0, sd=1)
+radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5)
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/trAsCov-class.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/trAsCov-class.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/trAsCov-class.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,38 @@
+\HeaderA{trAsCov-class}{Trace of asymptotic covariance}{trAsCov.Rdash.class}
+\keyword{classes}{trAsCov-class}
+\begin{Description}\relax
+Class of trace of asymptotic covariance.
+\end{Description}
+\begin{Section}{Objects from the Class}
+Objects can be created by calls of the form \code{new("trAsCov", ...)}.
+More frequently they are created via the generating function
+\code{trAsCov}.
+\end{Section}
+\begin{Section}{Slots}
+\describe{
+\item[\code{type}:] Object of class \code{"character"}:
+\dQuote{trace of asymptotic covariance}.
+}
+\end{Section}
+\begin{Section}{Extends}
+Class \code{"asRisk"}, directly.\\
+Class \code{"RiskType"}, by class \code{"asRisk"}.
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
+
+Kohl, M. (2005) \emph{Numerical Contributions to the Asymptotic Theory of Robustness}.
+Bayreuth: Dissertation.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{asRisk-class}{asRisk.Rdash.class}}, \code{\LinkA{trAsCov}{trAsCov}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+new("trAsCov")
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/latex/trFiCov-class.tex
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/latex/trFiCov-class.tex (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/latex/trFiCov-class.tex 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,36 @@
+\HeaderA{trFiCov-class}{Trace of finite-sample covariance}{trFiCov.Rdash.class}
+\keyword{classes}{trFiCov-class}
+\begin{Description}\relax
+Class of trace of finite-sample covariance.
+\end{Description}
+\begin{Section}{Objects from the Class}
+Objects can be created by calls of the form \code{new("trFiCov", ...)}.
+More frequently they are created via the generating function
+\code{trFiCov}.
+\end{Section}
+\begin{Section}{Slots}
+\describe{
+\item[\code{type}:] Object of class \code{"character"}:
+\dQuote{trace of finite-sample covariance}.
+}
+\end{Section}
+\begin{Section}{Extends}
+Class \code{"fiRisk"}, directly.\\
+Class \code{"RiskType"}, by class \code{"fiRisk"}.
+\end{Section}
+\begin{Author}\relax
+Matthias Kohl \email{Matthias.Kohl at stamats.de}
+\end{Author}
+\begin{References}\relax
+Ruckdeschel, P. and Kohl, M. (2005) How to approximate
+the finite sample risk of M-estimators.
+\end{References}
+\begin{SeeAlso}\relax
+\code{\LinkA{fiRisk-class}{fiRisk.Rdash.class}}, \code{\LinkA{trFiCov}{trFiCov}}
+\end{SeeAlso}
+\begin{Examples}
+\begin{ExampleCode}
+new("trFiCov")
+\end{ExampleCode}
+\end{Examples}
+
Added: pkg/ROptEst.Rcheck/ROptEst/man/ROptEst.Rd.gz
===================================================================
(Binary files differ)
Property changes on: pkg/ROptEst.Rcheck/ROptEst/man/ROptEst.Rd.gz
___________________________________________________________________
Name: svn:mime-type
+ application/octet-stream
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/BinomialModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/BinomialModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/BinomialModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,132 @@
+###############################################################################
+## Example: Binomial Family
+###############################################################################
+require(ROptEst)
+
+## generates Binomial Family with
+## m = 25 and probability of success theta = 0.25
+B <- BinomFamily(size = 25, prob = 0.25)
+B # show B
+plot(B) # plot of Binom(size = 25, prob = 0.25) and L_2 derivative
+checkL2deriv(B)
+
+## classical optimal IC
+IC0 <- optIC(model = B, risk = asCov())
+IC0 # show IC
+plot(IC0) # plot IC
+checkIC(IC0)
+Risks(IC0)
+
+## lower case radius
+lowerCaseRadius(L2Fam = B, neighbor = ContNeighborhood(), risk = asMSE())
+lowerCaseRadius(L2Fam = B, neighbor = TotalVarNeighborhood(), risk = asMSE())
+
+## L_2 family + infinitesimal neighborhood
+RobB1 <- InfRobModel(center = B, neighbor = ContNeighborhood(radius = 0.5))
+RobB1 # show RobB1
+(RobB2 <- InfRobModel(center = B, neighbor = TotalVarNeighborhood(radius = 0.5)))
+
+## MSE solution
+system.time(IC1 <- optIC(model=RobB1, risk=asMSE()), gcFirst = TRUE)
+IC1
+checkIC(IC1)
+Risks(IC1)
+getRiskIC(IC1, asBias(), ContNeighborhood()) # standardized bias
+getRiskIC(IC1, asMSE(), ContNeighborhood(radius = 0.5))
+
+(Cov1 <- getRiskIC(IC1, asCov()))
+(mse1 <- getRiskIC(IC1, asMSE(), TotalVarNeighborhood(radius = 0.5)))
+(bias1 <- getRiskIC(IC1, asBias(), TotalVarNeighborhood()))
+## only suboptimal -> ToDo-List
+addRisk(IC1) <- list(Cov1, mse1, bias1)
+Risks(IC1)
+plot(IC1)
+
+system.time(IC2 <- optIC(model=RobB2, risk=asMSE()), gcFirst = TRUE)
+IC2
+checkIC(IC2)
+Risks(IC2)
+getRiskIC(IC2, asMSE(), TotalVarNeighborhood(radius = 0.5))
+getRiskIC(IC2, asBias(), TotalVarNeighborhood())
+getRiskIC(IC2, asBias(), ContNeighborhood())
+Cov2 <- getRiskIC(IC2, asCov())
+addRisk(IC2) <- Cov2
+Risks(IC2)
+plot(IC2)
+
+## lower case solutions
+(IC3 <- optIC(model=RobB1, risk=asBias()))
+checkIC(IC3)
+Risks(IC3)
+plot(IC3)
+
+(IC4 <- optIC(model=RobB2, risk=asBias()))
+checkIC(IC4)
+Risks(IC4)
+plot(IC4)
+
+
+## Hampel solution
+(IC5 <- optIC(model=RobB1, risk=asHampel(bound=clip(IC1))))
+checkIC(IC5)
+Risks(IC5)
+plot(IC5)
+
+(IC6 <- optIC(model=RobB2, risk=asHampel(bound=Risks(IC2)$asBias), maxiter = 200))
+checkIC(IC6)
+Risks(IC6)
+plot(IC6)
+
+
+## radius minimax IC
+system.time(IC7 <- radiusMinimaxIC(L2Fam=B, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=1), gcFirst = TRUE)
+IC7
+checkIC(IC7)
+Risks(IC7)
+plot(IC7)
+
+system.time(IC8 <- radiusMinimaxIC(L2Fam=B, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=1), gcFirst = TRUE)
+IC8
+checkIC(IC8)
+Risks(IC8)
+plot(IC8)
+
+
+## least favorable radius
+## (may take quite some time!)
+system.time(r.rho1 <- leastFavorableRadius(L2Fam=B, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5), gcFirst = TRUE)
+r.rho1
+system.time(r.rho2 <- leastFavorableRadius(L2Fam=B, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), rho=0.5), gcFirst = TRUE)
+r.rho2
+
+## one-step estimation
+## 1. generate a contaminated sample
+ind <- rbinom(100, size=1, prob=0.05)
+x <- rbinom(100, size=25, prob=(1-ind)*0.25 + ind*0.75)
+
+## 2. Kolmogorov(-Smirnov) minimum distance estimator
+(est0 <- ksEstimator(x=x, Binom(size=25), param = "prob"))
+
+## 3. one-step estimation: radius known
+RobB3 <- InfRobModel(center=BinomFamily(size=25, prob=est0$prob),
+ neighbor=ContNeighborhood(radius=0.5))
+IC9 <- optIC(model=RobB3, risk=asMSE())
+(est1 <- oneStepEstimator(x, IC=IC9, start=est0$prob))
+
+RobB4 <- InfRobModel(center=BinomFamily(size=25, prob=est0$prob),
+ neighbor=TotalVarNeighborhood(radius=0.25))
+IC10 <- optIC(model=RobB4, risk=asMSE())
+(est1 <- oneStepEstimator(x, IC=IC10, start=est0$prob))
+
+## 4. one-step estimation: radius interval
+IC11 <- radiusMinimaxIC(L2Fam=BinomFamily(size=25, prob=est0$prob),
+ neighbor=ContNeighborhood(), risk=asMSE(), loRad=0, upRad=Inf)
+(est2 <- oneStepEstimator(x, IC=IC11, start=est0$prob))
+
+IC12 <- radiusMinimaxIC(L2Fam=BinomFamily(size=25, prob=est0$prob),
+ neighbor=TotalVarNeighborhood(), risk=asMSE(), loRad=0, upRad=Inf)
+(est2 <- oneStepEstimator(x, IC=IC12, start=est0$prob))
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/ExponentialScaleModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/ExponentialScaleModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/ExponentialScaleModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,88 @@
+###############################################################################
+## Example: Exponential Scale Family
+###############################################################################
+require(ROptEst)
+
+## generates Exponential Scale Family with rate = 1
+E1 <- ExpScaleFamily(rate = 1)
+E1 # show E1
+plot(E1) # plot of Exp(rate = 1) and L_2 derivative
+checkL2deriv(E1)
+
+# classical optimal IC
+E1.IC0 <- optIC(model = E1, risk = asCov())
+E1.IC0 # show IC
+checkIC(E1.IC0)
+Risks(E1.IC0)
+plot(E1.IC0) # plot IC
+
+# L_2 family + infinitesimal neighborhood
+E1.Rob1 <- InfRobModel(center = E1, neighbor = ContNeighborhood(radius = 0.5))
+E1.Rob1 # show E1.Rob1
+E1.Rob2 <- InfRobModel(center = E1, neighbor = TotalVarNeighborhood(radius = 0.5))
+
+# MSE solution
+(E1.IC1 <- optIC(model=E1.Rob1, risk=asMSE()))
+checkIC(E1.IC1)
+Risks(E1.IC1)
+plot(E1.IC1)
+(E1.IC2 <- optIC(model=E1.Rob2, risk=asMSE()))
+checkIC(E1.IC2)
+Risks(E1.IC2)
+plot(E1.IC2)
+
+# lower case solutions
+(E1.IC3 <- optIC(model=E1.Rob1, risk=asBias()))
+checkIC(E1.IC3)
+Risks(E1.IC3)
+plot(E1.IC3)
+(E1.IC4 <- optIC(model=E1.Rob2, risk=asBias()))
+checkIC(E1.IC4)
+Risks(E1.IC4)
+plot(E1.IC4)
+
+# Hampel solution
+(E1.IC5 <- optIC(model=E1.Rob1, risk=asHampel(bound=clip(E1.IC1))))
+checkIC(E1.IC5)
+Risks(E1.IC5)
+plot(E1.IC5)
+(E1.IC6 <- optIC(model=E1.Rob2, risk=asHampel(bound=Risks(E1.IC2)$asBias), maxiter = 200))
+checkIC(E1.IC6)
+Risks(E1.IC6)
+plot(E1.IC6)
+
+# radius minimax IC
+(E1.IC7 <- radiusMinimaxIC(L2Fam=E1, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=0.5))
+checkIC(E1.IC7)
+Risks(E1.IC7)
+(E1.IC8 <- radiusMinimaxIC(L2Fam=E1, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=0.5))
+checkIC(E1.IC8)
+Risks(E1.IC8)
+
+# least favorable radius
+# (may take quite some time!)
+(E1.r.rho1 <- leastFavorableRadius(L2Fam=E1, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5))
+(E1.r.rho2 <- leastFavorableRadius(L2Fam=E1, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), rho=1/3))
+
+## one-step estimation
+## 1. generate a contaminated sample
+ind <- rbinom(1e2, size=1, prob=0.05)
+E1.x <- rexp(1e2, rate=(1-ind)*2+ind*10)
+
+## 2. Kolmogorov(-Smirnov) minimum distance estimator
+(E1.est0 <- ksEstimator(x=E1.x, Exp()))
+
+## 3. one-step estimation: radius known
+E1.Rob3 <- InfRobModel(center=ExpScaleFamily(rate=E1.est0$rate),
+ neighbor=ContNeighborhood(radius=0.5))
+E1.IC9 <- optIC(model=E1.Rob3, risk=asMSE())
+(E1.est1 <- oneStepEstimator(E1.x, IC=E1.IC9, start=E1.est0$rate))
+
+## 4. one-step estimation: radius interval
+E1.IC10 <- radiusMinimaxIC(L2Fam=ExpScaleFamily(rate=E1.est0$rate),
+ neighbor=ContNeighborhood(), risk=asMSE(), loRad=0, upRad=Inf)
+(E1.est2 <- oneStepEstimator(E1.x, IC=E1.IC10, start=E1.est0$rate))
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/GammaModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/GammaModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/GammaModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,73 @@
+###############################################################################
+## Example: Gamma Family
+###############################################################################
+require(ROptEst)
+
+## generates Gamma Family with
+## scale = 1 and shape = 1
+G <- GammaFamily(scale = 1, shape = 2)
+G # show G
+plot(G) # plot of Gammad(scale = 1, shape = 2) and L_2 derivative
+checkL2deriv(G)
+
+## classical optimal IC
+IC0 <- optIC(model = G, risk = asCov())
+IC0 # show IC
+system.time(checkIC(IC0), gcFirst = TRUE)
+Risks(IC0)
+plot(IC0) # plot IC
+
+## L_2 family + infinitesimal neighborhood
+RobG1 <- InfRobModel(center = G, neighbor = ContNeighborhood(radius = 0.5))
+RobG1 # show RobB1
+
+## MSE solution
+system.time(IC1 <- optIC(model=RobG1, risk=asMSE()), gcFirst = TRUE)
+IC1
+checkIC(IC1)
+Risks(IC1)
+plot(IC1)
+x11()
+infoPlot(IC1)
+
+## lower case solutions
+system.time(IC2 <- optIC(model=RobG1, risk=asBias(), tol = 1e-10), gcFirst = TRUE)
+IC2
+checkIC(IC2)
+Risks(IC2)
+plot(IC2)
+x11()
+infoPlot(IC2)
+
+## Hampel solution
+system.time(IC3 <- optIC(model=RobG1, risk=asHampel(bound=clip(IC1))), gcFirst = TRUE)
+IC3
+checkIC(IC3)
+Risks(IC3)
+plot(IC3)
+x11()
+infoPlot(IC3)
+
+## radius minimax IC
+## takes quite some time - about 30 min.
+system.time(IC4 <- radiusMinimaxIC(L2Fam=G, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=Inf), gcFirst = TRUE)
+
+## least favorable radius
+## takes quite some time - several hours!
+#system.time(r.rho1 <- leastFavorableRadius(L2Fam=G, neighbor=ContNeighborhood(),
+# risk=asMSE(), rho=0.5))
+
+## one-step estimation
+## 1. generate a contaminated sample
+ind <- rbinom(100, size=1, prob=0.05)
+x <- (1-ind)*rgamma(100, scale = 1, shape = 2) + ind*10
+
+## 2. Kolmogorov(-Smirnov) minimum distance estimator
+(est0 <- ksEstimator(x=x, Gammad()))
+
+## 3. one-step estimation: radius known
+RobG3 <- InfRobModel(center=GammaFamily(scale = est0$scale, shape = est0$shape),
+ neighbor=ContNeighborhood(radius=0.5))
+IC9 <- optIC(model=RobG3, risk=asMSE())
+(est1 <- oneStepEstimator(x, IC=IC9, start=est0))
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/GumbelLocationModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/GumbelLocationModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/GumbelLocationModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,135 @@
+###############################################################################
+## Example: Gumbel Location Family
+## computations numerically less stable than in case of the
+## Exponential Scale Family
+###############################################################################
+require(ROptEst)
+
+## generates Gumbel Location Family with loc = 0
+## (known scale = 1)
+distrExOptions(ElowerTruncQuantile, 1e-15) # non-finite function value in integrate
+G0 <- GumbelLocationFamily(loc=0, scale=1)
+G0 # show G0
+plot(G0) # plot of Gumbel(loc = 0, scale = 1) and L_2 derivative
+checkL2deriv(G0)
+
+# classical optimal IC
+G0.IC0 <- optIC(model = G0, risk = asCov())
+G0.IC0 # show IC
+plot(G0.IC0) # plot IC
+checkIC(G0.IC0)
+Risks(G0.IC0)
+
+# L_2 family + infinitesimal neighborhood
+G0.Rob1 <- InfRobModel(center = G0, neighbor = ContNeighborhood(radius = 0.5))
+G0.Rob1 # show G0.Rob1
+G0.Rob2 <- InfRobModel(center = G0, neighbor = TotalVarNeighborhood(radius = 0.5))
+
+# MSE solution
+E1.Rob1 <- InfRobModel(center = ExpScaleFamily(), neighbor = ContNeighborhood(radius = 0.5))
+(E1.IC1 <- optIC(model=E1.Rob1, risk=asMSE()))
+G0.IC1 <- optIC(model=G0.Rob1, risk=asMSE())
+checkIC(G0.IC1)
+Risks(G0.IC1)
+clip(E1.IC1)
+cent(E1.IC1)
+stand(E1.IC1)
+clip(G0.IC1)
+cent(G0.IC1)
+stand(G0.IC1)
+# alternatively
+G0.IC11 <- E1.IC1 # rate = 1!
+CallL2Fam(G0.IC11) <- call("GumbelLocationFamily")
+cent(G0.IC11) <- -cent(E1.IC1)
+G0.IC11
+checkIC(G0.IC11)
+Risks(G0.IC11)
+
+E1.Rob2 <- InfRobModel(center = ExpScaleFamily(), neighbor = TotalVarNeighborhood(radius = 0.5))
+E1.IC2 <- optIC(model=E1.Rob2, risk=asMSE())
+#distrExOptions(ElowerTruncQuantile, 1e-15)
+G0.IC2 <- optIC(model=G0.Rob2, risk=asMSE())
+checkIC(G0.IC2)
+Risks(G0.IC2)
+clipLo(E1.IC2)
+clipUp(E1.IC2)
+stand(E1.IC2)
+clipLo(G0.IC2)
+clipUp(G0.IC2)
+stand(G0.IC2)
+# alternatively
+G0.IC21 <- E1.IC2 # rate = 1!
+CallL2Fam(G0.IC21) <- call("GumbelLocationFamily")
+clipLo(G0.IC21) <- -clipUp(E1.IC2)
+clipUp(G0.IC21) <- -clipLo(E1.IC2)
+G0.IC21
+checkIC(G0.IC21)
+Risks(G0.IC21)
+
+# lower case solutions
+(G0.IC3 <- optIC(model=G0.Rob1, risk=asBias()))
+checkIC(G0.IC3)
+Risks(G0.IC3)
+(G0.IC4 <- optIC(model=G0.Rob2, risk=asBias()))
+checkIC(G0.IC4)
+Risks(G0.IC4)
+
+# Hampel solution
+(G0.IC5 <- optIC(model=G0.Rob1, risk=asHampel(bound=clip(G0.IC1))))
+checkIC(G0.IC5)
+Risks(G0.IC5)
+(G0.IC6 <- optIC(model=G0.Rob2, risk=asHampel(bound=Risks(G0.IC2)$asBias), maxiter = 100))
+checkIC(G0.IC6)
+Risks(G0.IC6)
+
+# radius minimax IC
+# numerically instable for small 'loRad'!
+# => use connection to ExpScaleFamily for computations
+#(G0.IC7 <- radiusMinimaxIC(L2Fam=G0, neighbor=ContNeighborhood(),
+# risk=asMSE(), loRad=0.5, upRad=1.0))
+#checkIC(G0.IC7)
+#Risks(G0.IC7)
+#(G0.IC8 <- radiusMinimaxIC(L2Fam=G0, neighbor=TotalVarNeighborhood(),
+# risk=asMSE(), loRad=0.5, upRad=1.0))
+#checkIC(G0.IC8)
+#Risks(G0.IC8)
+
+# least favorable radius
+# numerically instable!
+# => use connection to ExpScaleFamily for computations
+#(G0.r.rho1 <- leastFavorableRadius(L2Fam=G0, neighbor=ContNeighborhood(),
+# risk=asMSE(), rho=0.5))
+#(G0.r.rho2 <- leastFavorableRadius(L2Fam=G0, neighbor=TotalVarNeighborhood(),
+# risk=asMSE(), rho=1/3))
+
+## one-step estimation
+## 1. generate a contaminated sample
+ind <- rbinom(1e2, size=1, prob=0.05)
+G0.x <- rgumbel(1e2, loc=(1-ind)*0.5+ind*1)
+
+## 2. Kolmogorov(-Smirnov) minimum distance estimator
+(G0.est0 <- ksEstimator(x=G0.x, Gumbel(), param = "loc"))
+
+## 3. one-step estimation: radius known
+G0.Rob3 <- InfRobModel(center=GumbelLocationFamily(loc=G0.est0$loc),
+ neighbor=ContNeighborhood(radius=0.5))
+G0.IC9 <- optIC(model=G0.Rob3, risk=asMSE())
+(G0.est1 <- oneStepEstimator(G0.x, IC=G0.IC9, start=G0.est0$loc))
+
+## 4. M estimation: radius known
+G0.Rob31 <- InfRobModel(center=GumbelLocationFamily(loc=0),
+ neighbor=ContNeighborhood(radius=0.5))
+G0.IC91 <- optIC(model=G0.Rob31, risk=asMSE())
+(G0.est11 <- locMEstimator(G0.x, IC=G0.IC91))
+
+## 5. one-step estimation: radius interval
+G0.IC10 <- radiusMinimaxIC(L2Fam=GumbelLocationFamily(loc=G0.est0$loc),
+ neighbor=ContNeighborhood(), risk=asMSE(), loRad=0.5, upRad=1)
+(G0.est2 <- oneStepEstimator(G0.x, IC=G0.IC10, start=G0.est0$loc))
+
+## 6. M estimation: radius interval
+G0.IC101 <- radiusMinimaxIC(L2Fam=GumbelLocationFamily(),
+ neighbor=ContNeighborhood(), risk=asMSE(), loRad=0.5, upRad=1)
+(G0.est21 <- locMEstimator(G0.x, IC=G0.IC101))
+
+distrExOptions(ElowerTruncQuantile, 0) # default
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/LognormalAndNormalModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/LognormalAndNormalModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/LognormalAndNormalModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,155 @@
+###############################################################################
+## Example: Lognormal Scale and Normal Location
+###############################################################################
+require(ROptEst)
+
+## generates Lognormal Scale Family with rate = 1
+LN1 <- LnormScaleFamily()
+LN1 # show LN1
+plot(LN1) # plot of Exp(rate = 1) and L_2 derivative
+checkL2deriv(LN1)
+
+## generates Normal Location Family with mean = 0
+N0 <- NormLocationFamily(mean=0, sd=1)
+N0 # show G0
+plot(N0) # plot of Norm(mean = 0, sd = 1) and L_2 derivative
+checkL2deriv(N0)
+
+
+# classical optimal IC
+LN1.IC0 <- optIC(model = LN1, risk = asCov())
+LN1.IC0 # show IC
+plot(LN1.IC0) # plot IC
+checkIC(LN1.IC0)
+Risks(LN1.IC0)
+N0.IC0 <- optIC(model = N0, risk = asCov())
+N0.IC0 # show IC
+plot(N0.IC0) # plot IC
+checkIC(N0.IC0)
+Risks(N0.IC0)
+
+
+# L_2 family + infinitesimal neighborhood
+LN1.Rob1 <- InfRobModel(center = LN1, neighbor = ContNeighborhood(radius = 0.5))
+LN1.Rob1 # show LN1.Rob1
+LN1.Rob2 <- InfRobModel(center = LN1, neighbor = TotalVarNeighborhood(radius = 0.25))
+N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 0.5))
+N0.Rob1 # show N0.Rob1
+N0.Rob2 <- InfRobModel(center = N0, neighbor = TotalVarNeighborhood(radius = 0.25))
+
+
+# MSE solution
+LN1.IC1 <- optIC(model=LN1.Rob1, risk=asMSE())
+checkIC(LN1.IC1)
+Risks(LN1.IC1)
+plot(LN1.IC1)
+
+N0.IC1 <- optIC(model=N0.Rob1, risk=asMSE())
+checkIC(N0.IC1)
+Risks(N0.IC1)
+plot(N0.IC1)
+
+clip(LN1.IC1)
+cent(LN1.IC1)
+stand(LN1.IC1)
+clip(N0.IC1)
+cent(N0.IC1)
+stand(N0.IC1)
+
+LN1.IC2 <- optIC(model=LN1.Rob2, risk=asMSE())
+checkIC(LN1.IC2)
+Risks(LN1.IC2)
+plot(LN1.IC2)
+
+N0.IC2 <- optIC(model=N0.Rob2, risk=asMSE())
+checkIC(N0.IC2)
+Risks(N0.IC2)
+plot(N0.IC2)
+
+clipLo(LN1.IC2)
+clipUp(LN1.IC2)
+stand(LN1.IC2)
+clipLo(N0.IC2)
+clipUp(N0.IC2)
+stand(N0.IC2)
+
+
+# lower case solutions
+LN1.IC3 <- optIC(model=LN1.Rob1, risk=asBias())
+checkIC(LN1.IC3)
+Risks(LN1.IC3)
+plot(LN1.IC3)
+
+N0.IC3 <- optIC(model=N0.Rob1, risk=asBias())
+checkIC(N0.IC3)
+Risks(N0.IC3)
+plot(N0.IC3)
+
+LN1.IC4 <- optIC(model=LN1.Rob2, risk=asBias())
+checkIC(LN1.IC4)
+Risks(LN1.IC4)
+plot(LN1.IC4)
+
+N0.IC4 <- optIC(model=N0.Rob2, risk=asBias())
+checkIC(N0.IC4)
+Risks(N0.IC4)
+plot(N0.IC4)
+
+
+# Hampel solution
+LN1.IC5 <- optIC(model=LN1.Rob1, risk=asHampel(bound=clip(LN1.IC1)))
+checkIC(LN1.IC5)
+Risks(LN1.IC5)
+plot(LN1.IC5)
+
+N0.IC5 <- optIC(model=N0.Rob1, risk=asHampel(bound=clip(N0.IC1)))
+checkIC(N0.IC5)
+Risks(N0.IC5)
+plot(N0.IC5)
+
+LN1.IC6 <- optIC(model=LN1.Rob2, risk=asHampel(bound=Risks(LN1.IC2)$asBias))
+checkIC(LN1.IC6)
+Risks(LN1.IC6)
+plot(LN1.IC6)
+
+N0.IC6 <- optIC(model=N0.Rob2, risk=asHampel(bound=Risks(N0.IC2)$asBias))
+checkIC(N0.IC6)
+Risks(N0.IC6)
+plot(N0.IC6)
+
+# radius minimax IC
+(LN1.IC7 <- radiusMinimaxIC(L2Fam=LN1, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=0.5))
+checkIC(LN1.IC7)
+Risks(LN1.IC7)
+plot(LN1.IC7)
+
+(N0.IC7 <- radiusMinimaxIC(L2Fam=N0, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5))
+checkIC(N0.IC7)
+Risks(N0.IC7)
+plot(N0.IC7)
+
+(LN1.IC8 <- radiusMinimaxIC(L2Fam=LN1, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=0.25))
+checkIC(LN1.IC8)
+Risks(LN1.IC8)
+plot(LN1.IC8)
+
+(N0.IC8 <- radiusMinimaxIC(L2Fam=N0, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=0.25))
+checkIC(N0.IC8)
+Risks(N0.IC8)
+plot(N0.IC8)
+
+
+# least favorable radius
+# (may take quite some time!)
+(LN1.r.rho1 <- leastFavorableRadius(L2Fam=LN1, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5))
+(N0.r.rho1 <- leastFavorableRadius(L2Fam=N0, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5))
+(LN1.r.rho2 <- leastFavorableRadius(L2Fam=LN1, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), rho=1/3))
+(N0.r.rho2 <- leastFavorableRadius(L2Fam=N0, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), rho=1/3))
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/NormalLocationScaleModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/NormalLocationScaleModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/NormalLocationScaleModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,79 @@
+###############################################################################
+## Example: Normal location and scale
+###############################################################################
+require(ROptEst)
+
+## generates normal location and scale family with mean = 0 and sd = 1
+N0 <- NormLocationScaleFamily(mean=0, sd=1)
+N0 # show G0
+plot(N0) # plot of Norm(mean = 0, sd = 1) and L_2 derivative
+checkL2deriv(N0)
+
+# classical optimal IC
+N0.IC0 <- optIC(model = N0, risk = asCov())
+N0.IC0 # show IC
+checkIC(N0.IC0)
+Risks(N0.IC0)
+plot(N0.IC0) # plot IC
+
+# L_2 family + infinitesimal neighborhood
+N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 0.5))
+N0.Rob1 # show N0.Rob1
+
+# MSE solution
+system.time(N0.IC1 <- optIC(model = N0.Rob1, risk = asMSE()), gcFirst = TRUE)
+checkIC(N0.IC1)
+Risks(N0.IC1)
+plot(N0.IC1)
+infoPlot(N0.IC1)
+
+# lower case solutions
+(N0.IC2 <- optIC(model = N0.Rob1, risk = asBias(), tol = 1e-10))
+checkIC(N0.IC2)
+Risks(N0.IC2)
+plot(N0.IC2)
+infoPlot(N0.IC2)
+
+# Hampel solution
+(N0.IC3 <- optIC(model = N0.Rob1, risk = asHampel(bound = clip(N0.IC1))))
+checkIC(N0.IC3)
+Risks(N0.IC3)
+plot(N0.IC3)
+infoPlot(N0.IC3)
+
+# radius minimax IC
+# (may take quite some time!)
+(N0.IC4 <- radiusMinimaxIC(L2Fam=N0, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=Inf))
+checkIC(N0.IC4)
+Risks(N0.IC4)
+plot(N0.IC4)
+infoPlot(N0.IC4)
+
+# least favorable radius
+# (may take quite some time!)
+#N0.r.rho1 <- leastFavorableRadius(L2Fam=N0, neighbor=ContNeighborhood(),
+# risk=asMSE(), rho=0.5)
+
+## one-step estimation
+## 1. generate a contaminated sample
+ind <- rbinom(100, size=1, prob=0.05)
+x <- rnorm(100, mean=0, sd=(1-ind) + ind*9)
+
+## 2. Kolmogorov(-Smirnov) minimum distance estimator
+(est0 <- ksEstimator(x=x, Norm()))
+
+## 3. one-step estimation: radius known
+N1 <- NormLocationScaleFamily(mean=est0$mean, sd=est0$sd)
+N1.Rob <- InfRobModel(center = N1, neighbor = ContNeighborhood(radius = 0.5))
+IC1 <- optIC(model = N1.Rob, risk = asMSE())
+(est1 <- oneStepEstimator(x, IC1, est0))
+
+## 4. one-step estimation: radius unknown
+## rough estimate: 1-10% contamination
+## => r\in[0.1,1.0]
+
+## takes some time
+IC2 <- radiusMinimaxIC(L2Fam=N1, neighbor=ContNeighborhood(),risk=asMSE(),
+ loRad=0.1, upRad=1.0)
+(est2 <- oneStepEstimator(x, IC2, est0))
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/NormalScaleModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/NormalScaleModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/NormalScaleModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,72 @@
+###############################################################################
+## Example: Normal Scale
+###############################################################################
+require(ROptEst)
+
+## generates Normal Scale Family with scale = 1
+N0 <- NormScaleFamily(mean=0, sd=1)
+N0 # show G0
+plot(N0) # plot of Norm(mean = 0, sd = 1) and L_2 derivative
+checkL2deriv(N0)
+
+# classical optimal IC
+N0.IC0 <- optIC(model = N0, risk = asCov())
+N0.IC0 # show IC
+plot(N0.IC0) # plot IC
+checkIC(N0.IC0)
+Risks(N0.IC0)
+
+# L_2 family + infinitesimal neighborhood
+N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 0.5))
+N0.Rob1 # show N0.Rob1
+N0.Rob2 <- InfRobModel(center = N0, neighbor = TotalVarNeighborhood(radius = 0.5))
+
+# MSE solution
+(N0.IC1 <- optIC(model=N0.Rob1, risk=asMSE()))
+checkIC(N0.IC1)
+Risks(N0.IC1)
+plot(N0.IC1)
+
+(N0.IC2 <- optIC(model=N0.Rob2, risk=asMSE()))
+checkIC(N0.IC2)
+Risks(N0.IC2)
+plot(N0.IC2)
+
+# lower case solutions
+(N0.IC3 <- optIC(model=N0.Rob1, risk=asBias()))
+checkIC(N0.IC3)
+Risks(N0.IC3)
+plot(N0.IC3)
+(N0.IC4 <- optIC(model=N0.Rob2, risk=asBias()))
+checkIC(N0.IC4)
+Risks(N0.IC4)
+plot(N0.IC4)
+
+# Hampel solution
+(N0.IC5 <- optIC(model=N0.Rob1, risk=asHampel(bound=clip(N0.IC1))))
+checkIC(N0.IC5)
+Risks(N0.IC5)
+plot(N0.IC5)
+(N0.IC6 <- optIC(model=N0.Rob2, risk=asHampel(bound=Risks(N0.IC2)$asBias), maxiter = 200))
+checkIC(N0.IC6)
+Risks(N0.IC6)
+plot(N0.IC6)
+
+# radius minimax IC
+(N0.IC7 <- radiusMinimaxIC(L2Fam=N0, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=Inf))
+checkIC(N0.IC7)
+Risks(N0.IC7)
+plot(N0.IC7)
+(N0.IC8 <- radiusMinimaxIC(L2Fam=N0, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=Inf))
+checkIC(N0.IC8)
+Risks(N0.IC8)
+plot(N0.IC8)
+
+# least favorable radius
+# (may take quite some time!)
+(N0.r.rho1 <- leastFavorableRadius(L2Fam=N0, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5))
+(N0.r.rho2 <- leastFavorableRadius(L2Fam=N0, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), rho=1/3))
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/PoissonModel.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/PoissonModel.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/PoissonModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,109 @@
+###############################################################################
+## Example: Poisson Family
+###############################################################################
+require(ROptEst)
+
+distroptions("TruncQuantile", 1e-10) # increases numerical support of Pois;
+ # i.e., increases precision of the
+ # computations
+## generates Poisson Family with theta = 4.5
+P <- PoisFamily(lambda = 4.5)
+P # show P
+plot(P) # plot of Pois(lambda = 4.5) and L_2 derivative
+checkL2deriv(P)
+
+# classical optimal IC
+IC0 <- optIC(model = P, risk = asCov())
+IC0 # show IC
+checkIC(IC0)
+Risks(IC0)
+plot(IC0) # plot IC
+
+# L_2 family + infinitesimal neighborhood
+RobP1 <- InfRobModel(center = P, neighbor = ContNeighborhood(radius = 0.5))
+RobP1 # show RobP1
+(RobP2 <- InfRobModel(center = P, neighbor = TotalVarNeighborhood(radius = 0.5)))
+
+## lower case radius
+lowerCaseRadius(L2Fam = P, ContNeighborhood(radius = 0.5), risk = asMSE())
+lowerCaseRadius(L2Fam = P, TotalVarNeighborhood(radius = 0.5), risk = asMSE())
+
+# MSE solution
+(IC1 <- optIC(model=RobP1, risk=asMSE()))
+checkIC(IC1)
+Risks(IC1)
+plot(IC1)
+
+(IC2 <- optIC(model=RobP2, risk=asMSE()))
+checkIC(IC2)
+Risks(IC2)
+plot(IC2)
+
+
+# lower case solutions
+(IC3 <- optIC(model=RobP1, risk=asBias()))
+checkIC(IC3)
+Risks(IC3)
+plot(IC3)
+
+(IC4 <- optIC(model=RobP2, risk=asBias()))
+checkIC(IC4)
+Risks(IC4)
+plot(IC4)
+
+# Hampel solution
+(IC5 <- optIC(model=RobP1, risk=asHampel(bound=clip(IC1))))
+checkIC(IC5)
+Risks(IC5)
+plot(IC5)
+
+(IC6 <- optIC(model=RobP2, risk=asHampel(bound=Risks(IC2)$asBias), maxiter = 200))
+checkIC(IC6)
+Risks(IC6)
+plot(IC6)
+
+
+# radius minimax IC
+(IC7 <- radiusMinimaxIC(L2Fam=P, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=0.5))
+checkIC(IC7)
+Risks(IC7)
+plot(IC7)
+
+(IC8 <- radiusMinimaxIC(L2Fam=P, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), loRad=0, upRad=Inf))
+checkIC(IC8)
+Risks(IC8)
+plot(IC8)
+
+# least favorable radius
+# (may take quite some time!)
+(r.rho1 <- leastFavorableRadius(L2Fam=P, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5))
+(r.rho2 <- leastFavorableRadius(L2Fam=P, neighbor=TotalVarNeighborhood(),
+ risk=asMSE(), rho=1/3))
+
+## one-step estimation
+## Example: Rutherford-Geiger (1910)
+## cf. Feller~(1968), Section VI.7 (a)
+x <- c(rep(0, 57), rep(1, 203), rep(2, 383), rep(3, 525), rep(4, 532),
+ rep(5, 408), rep(6, 273), rep(7, 139), rep(8, 45), rep(9, 27),
+ rep(10, 10), rep(11, 4), rep(12, 0), rep(13, 1), rep(14, 1))
+
+## 0. mean (classical optimal)
+(est0 <- mean(x))
+
+## 1. Kolmogorov(-Smirnov) minimum distance estimator
+(est1 <- ksEstimator(x=x, Pois()))
+
+## 2. one-step estimation: radius interval
+## 2.1 small amount of contamination < 2%
+IC9 <- radiusMinimaxIC(L2Fam=PoisFamily(lambda=est1$lambda),
+ neighbor=ContNeighborhood(), risk=asMSE(), loRad=0, upRad=1)
+(est21 <- oneStepEstimator(x, IC=IC9, start=est1$lambda))
+## 2.2 amount of contamination unknown
+IC10 <- radiusMinimaxIC(L2Fam=PoisFamily(lambda=est1$lambda),
+ neighbor=ContNeighborhood(), risk=asMSE(), loRad=0, upRad=Inf)
+(est22 <- oneStepEstimator(x, IC=IC10, start=est1$lambda))
+
+distroptions("TruncQuantile", 1e-5) # default
Added: pkg/ROptEst.Rcheck/ROptEst/scripts/UnderOverShootRisk.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/scripts/UnderOverShootRisk.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/scripts/UnderOverShootRisk.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,123 @@
+###############################################################################
+## Example: Normal Location
+###############################################################################
+system.time(require(ROptEst))
+
+## generates Normal Location Family with mean = 0
+N0 <- NormLocationFamily(mean=0)
+n <- 100
+tau <- qnorm(0.975)
+
+## classical optimal IC (radius = 0!)
+N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 0))
+N0.Rob2 <- InfRobModel(center = N0, neighbor = TotalVarNeighborhood(radius = 0))
+
+system.time(IC0c <- optIC(model=N0.Rob1, risk=asUnOvShoot(width = tau)), gcFirst = TRUE)
+checkIC(IC0c)
+Risks(IC0c)
+system.time(IC0v <- optIC(model=N0.Rob2, risk=asUnOvShoot(width = tau)), gcFirst = TRUE)
+checkIC(IC0v)
+Risks(IC0v)
+
+## boundary case
+N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 2*tau*1/sqrt(2*pi)))
+N0.Rob2 <- InfRobModel(center = N0, neighbor = TotalVarNeighborhood(radius = tau*1/sqrt(2*pi)))
+
+system.time(IC0c <- optIC(model=N0.Rob1, risk=asUnOvShoot(width = tau)), gcFirst = TRUE)
+checkIC(IC0c)
+Risks(IC0c)
+system.time(IC0v <- optIC(model=N0.Rob2, risk=asUnOvShoot(width = tau)), gcFirst = TRUE)
+checkIC(IC0v)
+Risks(IC0v)
+
+
+# L_2 family + infinitesimal resp. fixed neighborhood
+rad <- 0.5
+N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = rad))
+N0.Rob2 <- InfRobModel(center = N0, neighbor = TotalVarNeighborhood(radius = rad/2))
+N0.Rob3 <- FixRobModel(center = N0, neighbor = ContNeighborhood(radius = rad/sqrt(n)))
+N0.Rob4 <- FixRobModel(center = N0, neighbor = TotalVarNeighborhood(radius = rad/2/sqrt(n)))
+
+# asUnOvShoot solution
+N0.IC1 <- optIC(model = N0.Rob1, risk = asUnOvShoot(width = tau))
+checkIC(N0.IC1)
+Risks(N0.IC1)
+plot(N0.IC1)
+
+N0.IC2 <- optIC(model = N0.Rob2, risk = asUnOvShoot(width = tau))
+checkIC(N0.IC2)
+Risks(N0.IC2)
+plot(N0.IC2)
+
+# fiUnOvShoot solution
+N0.IC3 <- optIC(model=N0.Rob3, risk=fiUnOvShoot(width = tau/sqrt(n)), sampleSize = n)
+checkIC(N0.IC3)
+Risks(N0.IC3)
+plot(N0.IC3)
+
+N0.IC4 <- optIC(model=N0.Rob4, risk=fiUnOvShoot(width = tau/sqrt(n)), sampleSize = n)
+checkIC(N0.IC4)
+Risks(N0.IC4)
+plot(N0.IC4)
+
+# O(n^(-0.5))-corrected solution
+# in case of contamination neighborhoods
+N0.IC5 <- N0.IC1
+clipUp1 <- clipUp(N0.IC1)/as.vector(stand(N0.IC1))
+clipUp5 <- max(0, clipUp1 - rad*(rad + clipUp1*tau)/(sqrt(n)*2*tau*pnorm(-clipUp1)))
+stand5 <- 1/(2*pnorm(clipUp5)-1)
+clipUp(N0.IC5) <- stand5*clipUp5
+clipLo(N0.IC5) <- -clipUp(N0.IC5)
+stand(N0.IC5) <- as.matrix(stand5)
+Infos(N0.IC5) <- matrix(c("manually", "O(n^(-1/2))-corrected solution"), ncol=2,
+ dimnames=list(character(0), c("method", "message")))
+checkIC(N0.IC5)
+getRiskIC(N0.IC5, asUnOvShoot(width = tau), ContNeighborhood(radius=rad))
+getRiskIC(N0.IC5, fiUnOvShoot(width = tau/sqrt(n)), ContNeighborhood(radius=rad/sqrt(n)), sampleSize = n)
+
+# O(n^(-1))-corrected solution
+# in case of total variation neighborhoods
+N0.IC6 <- N0.IC2
+clipUp2 <- clipUp(N0.IC2)/as.vector(stand(N0.IC2))
+clipUp6 <- max(0, clipUp2 - tau*(2*clipUp2^2*rad/2 + tau*dnorm(clipUp2))/(6*n*pnorm(-clipUp2)))
+stand6 <- 1/(2*pnorm(clipUp6)-1)
+clipUp(N0.IC6) <- stand6*clipUp6
+clipLo(N0.IC6) <- -clipUp(N0.IC6)
+stand(N0.IC6) <- as.matrix(stand6)
+Infos(N0.IC6) <- matrix(c("manually", "O(n^(-1))-corrected solution"), ncol=2,
+ dimnames=list(character(0), c("method", "message")))
+checkIC(N0.IC6)
+getRiskIC(N0.IC6, asUnOvShoot(width = tau), TotalVarNeighborhood(radius=rad/2))
+getRiskIC(N0.IC6, fiUnOvShoot(width = tau/sqrt(n)), TotalVarNeighborhood(radius=rad/2/sqrt(n)), sampleSize = n)
+
+
+## estimation
+## 1. generate a contaminated sample
+ind <- rbinom(1e2, size = 1, prob = 0.05)
+X <- rnorm(1e2, mean = ind*4)
+summary(X)
+
+## 2. M estimation
+N0.Rob5 <- InfRobModel(center = NormLocationFamily(mean = 0),
+ neighbor = ContNeighborhood(radius = 0.5))
+N0.IC7 <- optIC(model=N0.Rob5, risk=asUnOvShoot(width = 1.960))
+(Mest1 <- locMEstimator(X, IC=N0.IC7))
+
+N0.Rob6 <- FixRobModel(center = NormLocationFamily(mean = 0),
+ neighbor = ContNeighborhood(radius = 0.05))
+N0.IC8 <- optIC(model = N0.Rob6, risk=fiUnOvShoot(width = 0.196), sampleSize = 1e2)
+(Mest2 <- locMEstimator(X, IC=N0.IC8))
+
+
+## 3. Kolmogorov(-Smirnov) minimum distance estimator
+(est0 <- ksEstimator(x=X, Norm(), param = "mean"))
+
+## 4. one-step estimation
+N0.Rob7 <- InfRobModel(center = NormLocationFamily(mean = est0$mean),
+ neighbor = ContNeighborhood(radius=0.5))
+N0.IC9 <- optIC(model=N0.Rob7, risk=asUnOvShoot(width = 1.960))
+(est1 <- oneStepEstimator(X, IC = N0.IC9, start = est0$mean))
+N0.Rob8 <- FixRobModel(center = NormLocationFamily(mean = est0$mean),
+ neighbor = ContNeighborhood(radius=0.05))
+N0.IC10 <- optIC(model=N0.Rob8, risk=fiUnOvShoot(width = 0.196), sampleSize = 1e2)
+(est2 <- oneStepEstimator(X, IC = N0.IC10, start = est0$mean))
Added: pkg/ROptEst.Rcheck/ROptEst/tests/tests.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst/tests/tests.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst/tests/tests.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,134 @@
+library(ROptEst)
+
+###############################################################################
+## start of tests
+###############################################################################
+
+## positive-definite, symmetric matrices
+new("PosDefSymmMatrix", diag(2))
+PosDefSymmMatrix(1)
+PosDefSymmMatrix(diag(3))
+
+
+## Distribution symmetry
+S1 <- new("NoSymmetry")
+type(S1)
+NoSymmetry()
+S2 <- new("EllipticalSymmetry", SymmCenter = 2)
+type(S2)
+EllipticalSymmetry(SymmCenter = 1)
+S3 <- new("SphericalSymmetry", SymmCenter = -2)
+type(S3)
+SphericalSymmetry(SymmCenter = c(0,0))
+new("DistrSymmList", list(S1, S2, S3))
+DistrSymmList(S1, S2, S3)
+
+## Distribution symmetry
+S4 <- new("NonSymmetric")
+type(S4)
+NonSymmetric()
+S5 <- new("EvenSymmetric", SymmCenter = -1)
+type(S5)
+EvenSymmetric(SymmCenter = 0)
+S6 <- new("OddSymmetric", SymmCenter = 3)
+type(S6)
+OddSymmetric(SymmCenter = c(1,1))
+new("FunSymmList", list(S4, S5, S6))
+FunSymmList(S4, S5, S6)
+
+
+## parametric family
+(PF <- new("ParamFamily"))
+plot(PF)
+ParamFamily()
+
+
+## L2-differentiable parametric family
+(L2PF <- new("L2ParamFamily"))
+plot(L2PF)
+L2ParamFamily()
+
+
+## simple L2-differentiable parametric families
+BinomFamily()
+BinomFamily(size = 10)
+BinomFamily(prob = 0.4)
+BinomFamily(size = 100, prob = 0.3)
+BinomFamily(size = 50, prob = 0.8, trafo = matrix(-1))
+
+PoisFamily()
+PoisFamily(lambda = 10)
+PoisFamily(lambda = 20, trafo = matrix(3))
+
+NormLocationFamily()
+NormLocationFamily(mean = 2)
+NormLocationFamily(sd = 0.1)
+NormLocationFamily(mean = -3, sd = 2)
+NormLocationFamily(mean = 1, sd = 0.5, trafo = matrix(-1))
+
+GumbelLocationFamily()
+GumbelLocationFamily(loc = -2)
+GumbelLocationFamily(scale = 2)
+GumbelLocationFamily(loc = 1, scale = 0.5)
+GumbelLocationFamily(loc = 10, scale = 10, trafo = matrix(0.5))
+
+NormScaleFamily()
+NormScaleFamily(sd = 3)
+NormScaleFamily(mean = 5)
+NormScaleFamily(sd = 0.1, mean = -3)
+NormScaleFamily(sd = 2.5, mean = 1, trafo = matrix(0.1))
+
+ExpScaleFamily()
+ExpScaleFamily(rate = 0.5)
+ExpScaleFamily(rate = 2, trafo = matrix(2))
+
+LnormScaleFamily()
+LnormScaleFamily(meanlog = 0.5)
+LnormScaleFamily(sdlog = 0.1)
+LnormScaleFamily(meanlog = -0.3, sdlog = 2)
+LnormScaleFamily(meanlog = 2, sdlog = 1.2, trafo = matrix(2.5))
+
+G1 <- GammaFamily()
+name(G1)
+name(G1) <- "standard Gamma family"
+name(G1)
+distribution(G1)
+(old <- props(G1))
+addProp(G1) <- "test"
+props(G1)
+props(G1) <- old
+props(G1)
+param(G1)
+main(G1)
+nuisance(G1)
+trafo(G1)
+L2deriv(G1)
+L2derivDistr(G1)
+L2derivSymm(G1)
+FisherInfo(G1)
+GammaFamily(scale = 2)
+GammaFamily(shape = 0.75)
+GammaFamily(scale = 1.5, shape = 2)
+GammaFamily(scale = 3, shape = 1.5, trafo = matrix(c(3, 0, 0, 1), ncol = 2))
+
+NormLocationScaleFamily()
+NormLocationScaleFamily(mean = 1)
+NormLocationScaleFamily(sd = 0.5)
+NormLocationScaleFamily(mean = -3, sd = 2)
+N1 <- NormLocationScaleFamily(mean = 2, sd = 0.1, trafo = matrix(c(1, 0), ncol = 2))
+plot(N1)
+
+## robust models
+new("FixRobModel")
+(RM1 <- FixRobModel(center = NormLocationFamily()))
+FixRobModel(center = PoisFamily(), neighbor = TotalVarNeighborhood(radius = 0.5))
+new("InfRobModel")
+(RM2 <- InfRobModel(center = NormLocationScaleFamily()))
+InfRobModel(center = BinomFamily(size=10), neighbor = TotalVarNeighborhood(radius = 0.2))
+
+
+###############################################################################
+## end of tests
+###############################################################################
+
+q("no")
Added: pkg/ROptEst.Rcheck/ROptEst-Ex.R
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst-Ex.R (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst-Ex.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,241 @@
+### * <HEADER>
+###
+attach(NULL, name = "CheckExEnv")
+assign("nameEx",
+ local({
+ s <- "__{must remake R-ex/*.R}__"
+ function(new) {
+ if(!missing(new)) s <<- new else s
+ }
+ }),
+ pos = "CheckExEnv")
+## Add some hooks to label plot pages for base and grid graphics
+assign("base_plot_hook",
+ function() {
+ pp <- par(c("mfg","mfcol","oma","mar"))
+ if(all(pp$mfg[1:2] == c(1, pp$mfcol[2]))) {
+ outer <- (oma4 <- pp$oma[4]) > 0; mar4 <- pp$mar[4]
+ mtext(sprintf("help(\"%s\")", nameEx()), side = 4,
+ line = if(outer)max(1, oma4 - 1) else min(1, mar4 - 1),
+ outer = outer, adj = 1, cex = .8, col = "orchid", las=3)
+ }
+ },
+ pos = "CheckExEnv")
+assign("grid_plot_hook",
+ function() {
+ pushViewport(viewport(width=unit(1, "npc") - unit(1, "lines"),
+ x=0, just="left"))
+ grid.text(sprintf("help(\"%s\")", nameEx()),
+ x=unit(1, "npc") + unit(0.5, "lines"),
+ y=unit(0.8, "npc"), rot=90,
+ gp=gpar(col="orchid"))
+ },
+ pos = "CheckExEnv")
+setHook("plot.new", get("base_plot_hook", pos = "CheckExEnv"))
+setHook("persp", get("base_plot_hook", pos = "CheckExEnv"))
+setHook("grid.newpage", get("grid_plot_hook", pos = "CheckExEnv"))
+assign("cleanEx",
+ function(env = .GlobalEnv) {
+ rm(list = ls(envir = env, all.names = TRUE), envir = env)
+ RNGkind("default", "default")
+ set.seed(1)
+ options(warn = 1)
+ .CheckExEnv <- as.environment("CheckExEnv")
+ delayedAssign("T", stop("T used instead of TRUE"),
+ assign.env = .CheckExEnv)
+ delayedAssign("F", stop("F used instead of FALSE"),
+ assign.env = .CheckExEnv)
+ sch <- search()
+ newitems <- sch[! sch %in% .oldSearch]
+ for(item in rev(newitems))
+ eval(substitute(detach(item), list(item=item)))
+ missitems <- .oldSearch[! .oldSearch %in% sch]
+ if(length(missitems))
+ warning("items ", paste(missitems, collapse=", "),
+ " have been removed from the search path")
+ },
+ pos = "CheckExEnv")
+assign("ptime", proc.time(), pos = "CheckExEnv")
+grDevices::postscript("ROptEst-Ex.ps")
+assign("par.postscript", graphics::par(no.readonly = TRUE), pos = "CheckExEnv")
+options(contrasts = c(unordered = "contr.treatment", ordered = "contr.poly"), pager="console")
+options(warn = 1)
+library('ROptEst')
+
+assign(".oldSearch", search(), pos = 'CheckExEnv')
+assign(".oldNS", loadedNamespaces(), pos = 'CheckExEnv')
+cleanEx(); nameEx("getL1normL2deriv")
+### * getL1normL2deriv
+
+flush(stderr()); flush(stdout())
+
+### Name: getL1normL2deriv
+### Title: Calculation of L1 norm of L2derivative
+### Aliases: getL1normL2deriv getL1normL2deriv-methods
+### getL1normL2deriv,UnivariateDistribution-method
+### getL1normL2deriv,RealRandVariable-method
+
+
+### ** Examples
+
+##
+
+
+
+cleanEx(); nameEx("getL2normL2deriv")
+### * getL2normL2deriv
+
+flush(stderr()); flush(stdout())
+
+### Name: getL2normL2deriv
+### Title: Calculation of L2 norm of L2derivative
+### Aliases: getL2normL2deriv
+
+
+### ** Examples
+
+##
+
+
+
+cleanEx(); nameEx("leastFavorableRadius")
+### * leastFavorableRadius
+
+flush(stderr()); flush(stdout())
+
+### Name: leastFavorableRadius
+### Title: Generic Function for the Computation of Least Favorable Radii
+### Aliases: leastFavorableRadius leastFavorableRadius-methods
+### leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method
+
+
+### ** Examples
+
+N <- NormLocationFamily(mean=0, sd=1)
+leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), rho=0.5)
+
+
+
+cleanEx(); nameEx("lowerCaseRadius")
+### * lowerCaseRadius
+
+flush(stderr()); flush(stdout())
+
+### Name: lowerCaseRadius
+### Title: Computation of the lower case radius
+### Aliases: lowerCaseRadius lowerCaseRadius-methods
+### lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,BiasType-method
+### lowerCaseRadius,L2ParamFamily,TotalVarNeighborhood,asMSE,BiasType-met
+### hod
+
+
+### ** Examples
+
+lowerCaseRadius(BinomFamily(size = 10), ContNeighborhood(), asMSE())
+lowerCaseRadius(BinomFamily(size = 10), TotalVarNeighborhood(), asMSE())
+
+
+
+cleanEx(); nameEx("optIC")
+### * optIC
+
+flush(stderr()); flush(stdout())
+
+### Name: optIC
+### Title: Generic function for the computation of optimally robust ICs
+### Aliases: optIC optIC-methods optIC,L2ParamFamily,asCov-method
+### optIC,InfRobModel,asRisk-method optIC,InfRobModel,asUnOvShoot-method
+### optIC,FixRobModel,fiUnOvShoot-method
+
+
+### ** Examples
+
+B <- BinomFamily(size = 25, prob = 0.25)
+
+## classical optimal IC
+IC0 <- optIC(model = B, risk = asCov())
+plot(IC0) # plot IC
+checkIC(IC0, B)
+
+
+
+cleanEx(); nameEx("optRisk")
+### * optRisk
+
+flush(stderr()); flush(stdout())
+
+### Name: optRisk
+### Title: Generic function for the computation of the minimal risk
+### Aliases: optRisk optRisk-methods optRisk,L2ParamFamily,asCov-method
+### optRisk,InfRobModel,asRisk-method
+### optRisk,FixRobModel,fiUnOvShoot-method
+
+
+### ** Examples
+
+optRisk(model = NormLocationScaleFamily(), risk = asCov())
+
+
+
+cleanEx(); nameEx("radiusMinimaxIC")
+### * radiusMinimaxIC
+
+flush(stderr()); flush(stdout())
+
+### Name: radiusMinimaxIC
+### Title: Generic function for the computation of the radius minimax IC
+### Aliases: radiusMinimaxIC radiusMinimaxIC-methods
+### radiusMinimaxIC,L2ParamFamily,UncondNeighborhood,asGRisk-method
+
+
+### ** Examples
+
+N <- NormLocationFamily(mean=0, sd=1)
+radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
+ risk=asMSE(), loRad=0.1, upRad=0.5)
+
+
+
+cleanEx(); nameEx("trAsCov-class")
+### * trAsCov-class
+
+flush(stderr()); flush(stdout())
+
+### Name: trAsCov-class
+### Title: Trace of asymptotic covariance
+### Aliases: trAsCov-class
+### Keywords: classes
+
+### ** Examples
+
+new("trAsCov")
+
+
+
+cleanEx(); nameEx("trFiCov-class")
+### * trFiCov-class
+
+flush(stderr()); flush(stdout())
+
+### Name: trFiCov-class
+### Title: Trace of finite-sample covariance
+### Aliases: trFiCov-class
+### Keywords: classes
+
+### ** Examples
+
+new("trFiCov")
+
+
+
+### * <FOOTER>
+###
+cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
+grDevices::dev.off()
+###
+### Local variables: ***
+### mode: outline-minor ***
+### outline-regexp: "\\(> \\)?### [*]+" ***
+### End: ***
+quit('no')
Added: pkg/ROptEst.Rcheck/ROptEst-Ex.Rout
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst-Ex.Rout (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst-Ex.Rout 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,192 @@
+
+R version 2.6.0 RC (2007-10-01 r43043)
+Copyright (C) 2007 The R Foundation for Statistical Computing
+ISBN 3-900051-07-0
+
+R ist freie Software und kommt OHNE JEGLICHE GARANTIE.
+Sie sind eingeladen, es unter bestimmten Bedingungen weiter zu verbreiten.
+Tippen Sie 'license()' or 'licence()' für Details dazu.
+
+R ist ein Gemeinschaftsprojekt mit vielen Beitragenden.
+Tippen Sie 'contributors()' für mehr Information und 'citation()',
+um zu erfahren, wie R oder R packages in Publikationen zitiert werden können.
+
+Tippen Sie 'demo()' für einige Demos, 'help()' für on-line Hilfe, oder
+'help.start()' für eine HTML Browserschnittstelle zur Hilfe.
+Tippen Sie 'q()', um R zu verlassen.
+
+> ### * <HEADER>
+> ###
+> attach(NULL, name = "CheckExEnv")
+> assign("nameEx",
++ local({
++ s <- "__{must remake R-ex/*.R}__"
++ function(new) {
++ if(!missing(new)) s <<- new else s
++ }
++ }),
++ pos = "CheckExEnv")
+> ## Add some hooks to label plot pages for base and grid graphics
+> assign("base_plot_hook",
++ function() {
++ pp <- par(c("mfg","mfcol","oma","mar"))
++ if(all(pp$mfg[1:2] == c(1, pp$mfcol[2]))) {
++ outer <- (oma4 <- pp$oma[4]) > 0; mar4 <- pp$mar[4]
++ mtext(sprintf("help(\"%s\")", nameEx()), side = 4,
++ line = if(outer)max(1, oma4 - 1) else min(1, mar4 - 1),
++ outer = outer, adj = 1, cex = .8, col = "orchid", las=3)
++ }
++ },
++ pos = "CheckExEnv")
+> assign("grid_plot_hook",
++ function() {
++ pushViewport(viewport(width=unit(1, "npc") - unit(1, "lines"),
++ x=0, just="left"))
++ grid.text(sprintf("help(\"%s\")", nameEx()),
++ x=unit(1, "npc") + unit(0.5, "lines"),
++ y=unit(0.8, "npc"), rot=90,
++ gp=gpar(col="orchid"))
++ },
++ pos = "CheckExEnv")
+> setHook("plot.new", get("base_plot_hook", pos = "CheckExEnv"))
+> setHook("persp", get("base_plot_hook", pos = "CheckExEnv"))
+> setHook("grid.newpage", get("grid_plot_hook", pos = "CheckExEnv"))
+> assign("cleanEx",
++ function(env = .GlobalEnv) {
++ rm(list = ls(envir = env, all.names = TRUE), envir = env)
++ RNGkind("default", "default")
++ set.seed(1)
++ options(warn = 1)
++ .CheckExEnv <- as.environment("CheckExEnv")
++ delayedAssign("T", stop("T used instead of TRUE"),
++ assign.env = .CheckExEnv)
++ delayedAssign("F", stop("F used instead of FALSE"),
++ assign.env = .CheckExEnv)
++ sch <- search()
++ newitems <- sch[! sch %in% .oldSearch]
++ for(item in rev(newitems))
++ eval(substitute(detach(item), list(item=item)))
++ missitems <- .oldSearch[! .oldSearch %in% sch]
++ if(length(missitems))
++ warning("items ", paste(missitems, collapse=", "),
++ " have been removed from the search path")
++ },
++ pos = "CheckExEnv")
+> assign("ptime", proc.time(), pos = "CheckExEnv")
+> grDevices::postscript("ROptEst-Ex.ps")
+> assign("par.postscript", graphics::par(no.readonly = TRUE), pos = "CheckExEnv")
+> options(contrasts = c(unordered = "contr.treatment", ordered = "contr.poly"), pager="console")
+> options(warn = 1)
+> library('ROptEst')
+Lade nötiges Paket: distr
+Warnung: Paket 'distr' wurde unter R Version 2.6.1 gebaut
+Lade nötiges Paket: startupmsg
+:startupmsg> Utilities for start-up messages (version 0.5)
+
+:startupmsg> For more information see ?"startupmsg", NEWS("startupmsg")
+:startupmsg>
+
+:distr> Object orientated implementation of distributions (version 2.0)
+
+:distr> Attention: Arithmetics on distribution objects are understood as
+:distr> operations on corresponding random variables (r.v.s); see distrARITH().
+:distr> Some functions from package 'stats' are intentionally masked
+:distr> ---see distrMASK().
+:distr> Note that global options are controlled by distroptions()
+:distr> ---c.f. ?"distroptions".
+
+:distr> For more information see ?"distr", NEWS("distr"), as well as
+:distr> http://distr.r-forge.r-project.org/
+:distr> Package "distrDoc" provides a vignette to this package as well as
+:distr> to several extension packages; try vignette("distr").
+:distr>
+
+Lade nötiges Paket: distrEx
+Lade nötiges Paket: evd
+:distrEx> Extensions of package distr (version 2.0)
+
+:distrEx> Note: Packages "e1071", "moments", "fBasics" should be attached
+:distrEx> /before/ package "distrEx". See distrExMASK().
+
+:distrEx> For more information see ?"distrEx", NEWS("distrEx"), as well as
+:distrEx> http://distr.r-forge.r-project.org/
+:distrEx> Package "distrDoc" provides a vignette to this package as well as
+:distrEx> to several related packages; try vignette("distr").
+:distrEx>
+
+Lade nötiges Paket: distrMod
+Lade nötiges Paket: RandVar
+:RandVar> Implementation of random variables (version 0.6.2)
+
+:RandVar> For more information see ?"RandVar", as well as
+:RandVar>
+:RandVar> http://www.uni-bayreuth.de/departments/math/org/mathe7/DISTR/RandVar.html
+:RandVar> This package also includes a vignette; try vignette("RandVar").
+:RandVar>
+
+:distrMod> Object orientated implementation of probability models (version 2.0)
+
+:distrMod> For more information see ?"distrMod", as well as
+:distrMod> http://distr.r-forge.r-project.org/
+:distrMod> Package "distrDoc" provides a vignette to this package as well as
+:distrMod> to several related packages; try vignette("distr").
+:distrMod>
+
+Lade nötiges Paket: RobAStBase
+>
+> assign(".oldSearch", search(), pos = 'CheckExEnv')
+> assign(".oldNS", loadedNamespaces(), pos = 'CheckExEnv')
+> cleanEx(); nameEx("getL1normL2deriv")
+> ### * getL1normL2deriv
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: getL1normL2deriv
+> ### Title: Calculation of L1 norm of L2derivative
+> ### Aliases: getL1normL2deriv getL1normL2deriv-methods
+> ### getL1normL2deriv,UnivariateDistribution-method
+> ### getL1normL2deriv,RealRandVariable-method
+>
+>
+> ### ** Examples
+>
+> ##
+>
+>
+>
+> cleanEx(); nameEx("getL2normL2deriv")
+> ### * getL2normL2deriv
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: getL2normL2deriv
+> ### Title: Calculation of L2 norm of L2derivative
+> ### Aliases: getL2normL2deriv
+>
+>
+> ### ** Examples
+>
+> ##
+>
+>
+>
+> cleanEx(); nameEx("leastFavorableRadius")
+> ### * leastFavorableRadius
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: leastFavorableRadius
+> ### Title: Generic Function for the Computation of Least Favorable Radii
+> ### Aliases: leastFavorableRadius leastFavorableRadius-methods
+> ### leastFavorableRadius,L2ParamFamily,UncondNeighborhood,asGRisk-method
+>
+>
+> ### ** Examples
+>
+> N <- NormLocationFamily(mean=0, sd=1)
+> leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
++ risk=asMSE(), rho=0.5)
+Fehler in uniroot(getIneffDiff, lower = lower, upper = upper, tol = .Machine$double.eps^0.25, :
+ f() values at end points not of opposite sign
+Calls: leastFavorableRadius ... leastFavorableRadius -> .local -> optimize -> <Anonymous> -> f -> uniroot
+Ausführung angehalten
Added: pkg/ROptEst.Rcheck/ROptEst-Ex.ps
===================================================================
--- pkg/ROptEst.Rcheck/ROptEst-Ex.ps (rev 0)
+++ pkg/ROptEst.Rcheck/ROptEst-Ex.ps 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,121 @@
+%!PS-Adobe-3.0
+%%DocumentNeededResources: font Helvetica
+%%+ font Helvetica-Bold
+%%+ font Helvetica-Oblique
+%%+ font Helvetica-BoldOblique
+%%+ font Symbol
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+%%Title: R Graphics Output
+%%Creator: R Software
+%%Pages: (atend)
+%%Orientation: Landscape
+%%BoundingBox: 18 18 577 824
+%%EndComments
+%%BeginProlog
+/bp { gs 595.00 0 translate 90 rotate gs } def
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+ /Agrave /Aacute /Acircumflex /Atilde /Adieresis /Aring /AE /Ccedilla
+ /Egrave /Eacute /Ecircumflex /Edieresis /Igrave /Iacute /Icircumflex /Idieresis
+ /Eth /Ntilde /Ograve /Oacute /Ocircumflex /Otilde /Odieresis /multiply
+ /Oslash /Ugrave /Uacute /Ucircumflex /Udieresis /Yacute /Thorn /germandbls
+ /agrave /aacute /acircumflex /atilde /adieresis /aring /ae /ccedilla
+ /egrave /eacute /ecircumflex /edieresis /igrave /iacute /icircumflex /idieresis
+ /eth /ntilde /ograve /oacute /ocircumflex /otilde /odieresis /divide
+ /oslash /ugrave /uacute /ucircumflex /udieresis /yacute /thorn /ydieresis
+]
+ def
+% end encoding
+%%IncludeResource: font Helvetica
+/Helvetica findfont
+dup length dict begin
+ {1 index /FID ne {def} {pop pop} ifelse} forall
+ /Encoding WinAnsiEncoding def
+ currentdict
+ end
+/Font1 exch definefont pop
+%%IncludeResource: font Helvetica-Bold
+/Helvetica-Bold findfont
+dup length dict begin
+ {1 index /FID ne {def} {pop pop} ifelse} forall
+ /Encoding WinAnsiEncoding def
+ currentdict
+ end
+/Font2 exch definefont pop
+%%IncludeResource: font Helvetica-Oblique
+/Helvetica-Oblique findfont
+dup length dict begin
+ {1 index /FID ne {def} {pop pop} ifelse} forall
+ /Encoding WinAnsiEncoding def
+ currentdict
+ end
+/Font3 exch definefont pop
+%%IncludeResource: font Helvetica-BoldOblique
+/Helvetica-BoldOblique findfont
+dup length dict begin
+ {1 index /FID ne {def} {pop pop} ifelse} forall
+ /Encoding WinAnsiEncoding def
+ currentdict
+ end
+/Font4 exch definefont pop
+%%IncludeResource: font Symbol
+/Symbol findfont
+dup length dict begin
+ {1 index /FID ne {def} {pop pop} ifelse} forall
+ currentdict
+ end
+/Font5 exch definefont pop
+%%EndProlog
+ep
+%%Trailer
+%%Pages: 0
+%%EOF
Modified: pkg/RobAStBase/NAMESPACE
===================================================================
--- pkg/RobAStBase/NAMESPACE 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/NAMESPACE 2008-02-16 03:32:41 UTC (rev 25)
@@ -54,27 +54,6 @@
"neighborRadius", "neighborRadius<-",
"clipLo", "clipLo<-",
"clipUp", "clipUp<-")
-exportMethods("optIC",
- "getInfRobIC",
- "getFixRobIC",
- "getAsRisk",
- "getFiRisk",
- "getInfClip",
- "getFixClip",
- "getInfGamma",
- "getInfCent",
- "getInfStand",
- "getRiskIC",
- "optRisk",
- "radiusMinimaxIC",
- "getIneffDiff",
- "leastFavorableRadius",
- "lowerCaseRadius")
-exportMethods("ksEstimator",
- "oneStepEstimator",
- "locMEstimator")
-exportMethods("nu", "nu<-", "name", "name<-",
- "sign", "sign<-")
export("ContNeighborhood", "TotalVarNeighborhood")
export("FixRobModel", "InfRobModel")
export("InfluenceCurve",
Modified: pkg/RobAStBase/R/FixRobModel.R
===================================================================
--- pkg/RobAStBase/R/FixRobModel.R 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/R/FixRobModel.R 2008-02-16 03:32:41 UTC (rev 25)
@@ -1,5 +1,7 @@
## Generating function
-FixRobModel <- function(center = ParamFamily(), neighbor = ContNeighborhood()){
+FixRobModel <- function(center = ParamFamily(modifyParam =
+ function(theta) Norm(mean = theta)),
+ neighbor = ContNeighborhood()){
if(!is(neighbor, "UncondNeighborhood"))
stop("'neighbor' is no unconditional neighborhood")
if(any(neighbor at radius < 0 || neighbor at radius > 1))
Added: pkg/RobAStBase/chm/00Index.html
===================================================================
--- pkg/RobAStBase/chm/00Index.html (rev 0)
+++ pkg/RobAStBase/chm/00Index.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,327 @@
+<html><head><title>Robust Asymptotic Statistics</title>
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head><body>
+<h1>Robust Asymptotic Statistics
+<img class="toplogo" src="logo.jpg" alt="[R logo]"></h1>
+
+<hr>
+
+<object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value=".. contents">
+</object>
+
+<h2>Help pages for package ‘RobAStBase’ version 0.1.0</h2>
+
+<p align="center">
+<a href="#A">A</a>
+<a href="#C">C</a>
+<a href="#D">D</a>
+<a href="#E">E</a>
+<a href="#F">F</a>
+<a href="#G">G</a>
+<a href="#I">I</a>
+<a href="#L">L</a>
+<a href="#M">M</a>
+<a href="#N">N</a>
+<a href="#O">O</a>
+<a href="#P">P</a>
+<a href="#R">R</a>
+<a href="#S">S</a>
+<a href="#T">T</a>
+<a href="#U">U</a>
+</p>
+<table width="100%">
+</table>
+
+<h2><a name="A">-- A --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="InfluenceCurve-class.html">addInfo<-,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">addRisk<-,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+</table>
+
+<h2><a name="C">-- C --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="IC-class.html">CallL2Fam</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="IC-class.html">CallL2Fam,IC-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">CallL2Fam<-,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="IC-class.html">CallL2Fam<-,IC-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">CallL2Fam<-,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">cent</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">cent,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">cent<-,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">center</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">center,RobModel-method</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">center<-,RobModel-method</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="checkIC.html">checkIC</a></td>
+<td>Generic Function for Checking ICs</td></tr>
+<tr><td width="25%"><a href="IC-class.html">checkIC,IC,L2ParamFamily-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="IC-class.html">checkIC,IC,missing-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">clip</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">clip,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">clip<-,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">clipLo</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">clipLo,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">clipLo<-,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">clipUp</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">clipUp,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">clipUp<-,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="ContIC.html">ContIC</a></td>
+<td>Generating function for ContIC-class</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">ContIC-class</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContNeighborhood.html">ContNeighborhood</a></td>
+<td>Generating function for ContNeighborhood-class</td></tr>
+<tr><td width="25%"><a href="ContNeighborhood-class.html">ContNeighborhood-class</a></td>
+<td>Contamination Neighborhood</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Curve</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Curve,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+</table>
+
+<h2><a name="D">-- D --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Domain,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+</table>
+
+<h2><a name="E">-- E --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="evalIC.html">evalIC</a></td>
+<td>Generic function for evaluating ICs</td></tr>
+<tr><td width="25%"><a href="IC-class.html">evalIC,IC,matrix-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="IC-class.html">evalIC,IC,numeric-method</a></td>
+<td>Influence curve</td></tr>
+</table>
+
+<h2><a name="F">-- F --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="FixRobModel.html">FixRobModel</a></td>
+<td>Generating function for FixRobModel-class</td></tr>
+<tr><td width="25%"><a href="FixRobModel-class.html">FixRobModel-class</a></td>
+<td>Robust model with fixed (unconditional) neighborhood</td></tr>
+</table>
+
+<h2><a name="G">-- G --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="generateIC.html">generateIC</a></td>
+<td>Generic function for the generation of influence curves</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">generateIC,ContNeighborhood,L2ParamFamily-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">generateIC,TotalVarNeighborhood,L2ParamFamily-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+</table>
+
+<h2><a name="I">-- I --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="IC.html">IC</a></td>
+<td>Generating function for IC-class</td></tr>
+<tr><td width="25%"><a href="IC-class.html">IC-class</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve.html">InfluenceCurve</a></td>
+<td>Generating function for InfluenceCurve-class</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="infoPlot.html">infoPlot</a></td>
+<td>Plot absolute and relative information</td></tr>
+<tr><td width="25%"><a href="IC-class.html">infoPlot,IC-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Infos</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Infos,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Infos<-,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfRobModel.html">InfRobModel</a></td>
+<td>Generating function for InfRobModel-class</td></tr>
+<tr><td width="25%"><a href="InfRobModel-class.html">InfRobModel-class</a></td>
+<td>Robust model with infinitesimal (unconditional) neighborhood</td></tr>
+</table>
+
+<h2><a name="L">-- L --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="locMEstimator.html">locMEstimator</a></td>
+<td>Generic function for the computation of location M estimators</td></tr>
+<tr><td width="25%"><a href="locMEstimator.html">locMEstimator,numeric,InfluenceCurve-method</a></td>
+<td>Generic function for the computation of location M estimators</td></tr>
+<tr><td width="25%"><a href="locMEstimator.html">locMEstimator-methods</a></td>
+<td>Generic function for the computation of location M estimators</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">lowerCase</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">lowerCase,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">lowerCase,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">lowerCase<-,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">lowerCase<-,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+</table>
+
+<h2><a name="M">-- M --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Map,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+</table>
+
+<h2><a name="N">-- N --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="InfluenceCurve-class.html">name,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">name,RobModel-method</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">name<-,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">neighbor</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">neighbor,RobModel-method</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="FixRobModel-class.html">neighbor<-,FixRobModel-method</a></td>
+<td>Robust model with fixed (unconditional) neighborhood</td></tr>
+<tr><td width="25%"><a href="InfRobModel-class.html">neighbor<-,InfRobModel-method</a></td>
+<td>Robust model with infinitesimal (unconditional) neighborhood</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">neighbor<-,RobModel-method</a></td>
+<td>Robust model</td></tr>
+<tr><td width="25%"><a href="Neighborhood-class.html">Neighborhood-class</a></td>
+<td>Neighborhood</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">neighborRadius</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">neighborRadius,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">neighborRadius,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">neighborRadius<-,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">neighborRadius<-,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+</table>
+
+<h2><a name="O">-- O --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator</a></td>
+<td>Generic function for the computation of one-step estimators</td></tr>
+<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,matrix,InfluenceCurve,list-method</a></td>
+<td>Generic function for the computation of one-step estimators</td></tr>
+<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,matrix,InfluenceCurve,numeric-method</a></td>
+<td>Generic function for the computation of one-step estimators</td></tr>
+<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,numeric,InfluenceCurve,list-method</a></td>
+<td>Generic function for the computation of one-step estimators</td></tr>
+<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator,numeric,InfluenceCurve,numeric-method</a></td>
+<td>Generic function for the computation of one-step estimators</td></tr>
+<tr><td width="25%"><a href="oneStepEstimator.html">oneStepEstimator-methods</a></td>
+<td>Generic function for the computation of one-step estimators</td></tr>
+</table>
+
+<h2><a name="P">-- P --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="IC-class.html">plot,IC-method</a></td>
+<td>Influence curve</td></tr>
+</table>
+
+<h2><a name="R">-- R --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="Neighborhood-class.html">radius</a></td>
+<td>Neighborhood</td></tr>
+<tr><td width="25%"><a href="Neighborhood-class.html">radius,Neighborhood-method</a></td>
+<td>Neighborhood</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Range,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Risks</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Risks,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">Risks<-,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="RobModel-class.html">RobModel-class</a></td>
+<td>Robust model</td></tr>
+</table>
+
+<h2><a name="S">-- S --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="ContIC-class.html">show,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="FixRobModel-class.html">show,FixRobModel-method</a></td>
+<td>Robust model with fixed (unconditional) neighborhood</td></tr>
+<tr><td width="25%"><a href="IC-class.html">show,IC-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfluenceCurve-class.html">show,InfluenceCurve-method</a></td>
+<td>Influence curve</td></tr>
+<tr><td width="25%"><a href="InfRobModel-class.html">show,InfRobModel-method</a></td>
+<td>Robust model with infinitesimal (unconditional) neighborhood</td></tr>
+<tr><td width="25%"><a href="Neighborhood-class.html">show,Neighborhood-method</a></td>
+<td>Neighborhood</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">show,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">stand</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">stand,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">stand,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="ContIC-class.html">stand<-,ContIC-method</a></td>
+<td>Influence curve of contamination type</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">stand<-,TotalVarIC-method</a></td>
+<td>Influence curve of total variation type</td></tr>
+</table>
+
+<h2><a name="T">-- T --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="TotalVarIC.html">TotalVarIC</a></td>
+<td>Generating function for TotalVarIC-class</td></tr>
+<tr><td width="25%"><a href="TotalVarIC-class.html">TotalVarIC-class</a></td>
+<td>Influence curve of total variation type</td></tr>
+<tr><td width="25%"><a href="TotalVarNeighborhood.html">TotalVarNeighborhood</a></td>
+<td>Generating function for TotalVarNeighborhood-class</td></tr>
+<tr><td width="25%"><a href="TotalVarNeighborhood-class.html">TotalVarNeighborhood-class</a></td>
+<td>Total variation neighborhood</td></tr>
+<tr><td width="25%"><a href="Neighborhood-class.html">type,Neighborhood-method</a></td>
+<td>Neighborhood</td></tr>
+</table>
+
+<h2><a name="U">-- U --</a></h2>
+
+<table width="100%">
+<tr><td width="25%"><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></td>
+<td>Unconditional neighborhood</td></tr>
+</table>
+</body></html>
Added: pkg/RobAStBase/chm/ContIC-class.html
===================================================================
--- pkg/RobAStBase/chm/ContIC-class.html (rev 0)
+++ pkg/RobAStBase/chm/ContIC-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,212 @@
+<html><head><title>Influence curve of contamination type</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>ContIC-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: ContIC-class">
+<param name="keyword" value="R: CallL2Fam<-,ContIC-method">
+<param name="keyword" value="R: cent">
+<param name="keyword" value="R: cent,ContIC-method">
+<param name="keyword" value="R: cent<-">
+<param name="keyword" value="R: cent<-,ContIC-method">
+<param name="keyword" value="R: clip">
+<param name="keyword" value="R: clip,ContIC-method">
+<param name="keyword" value="R: clip<-">
+<param name="keyword" value="R: clip<-,ContIC-method">
+<param name="keyword" value="R: lowerCase">
+<param name="keyword" value="R: lowerCase,ContIC-method">
+<param name="keyword" value="R: lowerCase<-">
+<param name="keyword" value="R: lowerCase<-,ContIC-method">
+<param name="keyword" value="R: neighborRadius">
+<param name="keyword" value="R: neighborRadius,ContIC-method">
+<param name="keyword" value="R: neighborRadius<-">
+<param name="keyword" value="R: neighborRadius<-,ContIC-method">
+<param name="keyword" value="R: stand">
+<param name="keyword" value="R: stand,ContIC-method">
+<param name="keyword" value="R: stand<-">
+<param name="keyword" value="R: stand<-,ContIC-method">
+<param name="keyword" value="R: generateIC,ContNeighborhood,L2ParamFamily-method">
+<param name="keyword" value="R: show,ContIC-method">
+<param name="keyword" value=" Influence curve of contamination type">
+</object>
+
+
+<h2>Influence curve of contamination type</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of (partial) influence curves of contamination type;
+i.e., influence curves <i>eta</i> of the form
+</p><p align="center"><i>eta = (A Lambda - a)min(1, b/|A Lambda - a|)</i></p><p>
+with clipping bound <i>b</i>, centering constant <i>a</i> and
+standardizing matrix <i>A</i>. <i>Lambda</i> stands for
+the L2 derivative of the corresponding L2 differentiable
+parametric family created via the call in the slot <code>CallL2Fam</code>.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("ContIC", ...)</code>.
+More frequently they are created via the generating function
+<code>ContIC</code>, respectively via the method <code>generateIC</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>CallL2Fam</code>:</dt><dd>object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </dd>
+
+
+<dt><code>name</code>:</dt><dd>object of class <code>"character"</code> </dd>
+
+
+<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code></dd>
+
+
+<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </dd>
+
+
+<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
+with two columns named <code>method</code> and <code>message</code>:
+additional informations. </dd>
+
+
+<dt><code>clip</code>:</dt><dd>object of class <code>"numeric"</code>:
+clipping bound. </dd>
+
+
+<dt><code>cent</code>:</dt><dd>object of class <code>"numeric"</code>:
+centering constant. </dd>
+
+
+<dt><code>stand</code>:</dt><dd>object of class <code>"matrix"</code>:
+standardizing matrix. </dd>
+
+
+<dt><code>lowerCase</code>:</dt><dd>object of class <code>"OptionalNumeric"</code>:
+optional constant for lower case solution. </dd>
+
+
+<dt><code>neighborRadius</code>:</dt><dd>object of class <code>"numeric"</code>:
+radius of the corresponding (unconditional) contamination
+neighborhood. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"IC"</code>, directly.<br>
+Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+<dt>CallL2Fam<-</dt><dd><code>signature(object = "ContIC")</code>:
+replacement function for slot <code>CallL2Fam</code>. </dd>
+
+
+<dt>cent</dt><dd><code>signature(object = "ContIC")</code>:
+accessor function for slot <code>cent</code>. </dd>
+
+
+<dt>cent<-</dt><dd><code>signature(object = "ContIC")</code>:
+replacement function for slot <code>cent</code>. </dd>
+
+
+<dt>clip</dt><dd><code>signature(object = "ContIC")</code>:
+accessor function for slot <code>clip</code>. </dd>
+
+
+<dt>clip<-</dt><dd><code>signature(object = "ContIC")</code>:
+replacement function for slot <code>clip</code>. </dd>
+
+
+<dt>stand</dt><dd><code>signature(object = "ContIC")</code>:
+accessor function for slot <code>stand</code>. </dd>
+
+
+<dt>stand<-</dt><dd><code>signature(object = "ContIC")</code>:
+replacement function for slot <code>stand</code>. </dd>
+
+
+<dt>lowerCase</dt><dd><code>signature(object = "ContIC")</code>:
+accessor function for slot <code>lowerCase</code>. </dd>
+
+
+<dt>lowerCase<-</dt><dd><code>signature(object = "ContIC")</code>:
+replacement function for slot <code>lowerCase</code>. </dd>
+
+
+<dt>neighborRadius</dt><dd><code>signature(object = "ContIC")</code>:
+accessor function for slot <code>neighborRadius</code>. </dd>
+
+
+<dt>neighborRadius<-</dt><dd><code>signature(object = "ContIC")</code>:
+replacement function for slot <code>neighborRadius</code>. </dd>
+
+
+<dt>generateIC</dt><dd><code>signature(neighbor = "ContNeighborhood", L2Fam = "L2ParamFamily")</code>:
+generate an object of class <code>"ContIC"</code>. Rarely called directly. </dd>
+
+
+<dt>show</dt><dd><code>signature(object = "ContIC")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- new("ContIC")
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/ContIC.html
===================================================================
--- pkg/RobAStBase/chm/ContIC.html (rev 0)
+++ pkg/RobAStBase/chm/ContIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,130 @@
+<html><head><title>Generating function for ContIC-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>ContIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: ContIC">
+<param name="keyword" value=" Generating function for ContIC-class">
+</object>
+
+
+<h2>Generating function for ContIC-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"ContIC"</code>;
+i.e., an influence curves <i>eta</i> of the form
+</p><p align="center"><i>eta = (A Lambda - a)min(1, b/|A Lambda - a|)</i></p><p>
+with clipping bound <i>b</i>, centering constant <i>a</i> and
+standardizing matrix <i>A</i>. <i>Lambda</i> stands for
+the L2 derivative of the corresponding L2 differentiable
+parametric family which can be created via <code>CallL2Fam</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+ContIC(name, CallL2Fam = call("L2ParamFamily"),
+ Curve = EuclRandVarList(RealRandVariable(Map = c(function(x){x}),
+ Domain = Reals())),
+ Risks, Infos, clip = Inf, cent = 0, stand = as.matrix(1),
+ lowerCase = NULL, neighborRadius = 0)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>name</code></td>
+<td>
+object of class <code>"character"</code>. </td></tr>
+<tr valign="top"><td><code>CallL2Fam</code></td>
+<td>
+object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </td></tr>
+<tr valign="top"><td><code>Curve</code></td>
+<td>
+object of class <code>"EuclRandVarList"</code> </td></tr>
+<tr valign="top"><td><code>Risks</code></td>
+<td>
+object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </td></tr>
+<tr valign="top"><td><code>Infos</code></td>
+<td>
+matrix of characters with two columns
+named <code>method</code> and <code>message</code>: additional informations. </td></tr>
+<tr valign="top"><td><code>clip</code></td>
+<td>
+positive real: clipping bound. </td></tr>
+<tr valign="top"><td><code>cent</code></td>
+<td>
+real: centering constant </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+matrix: standardizing matrix </td></tr>
+<tr valign="top"><td><code>lowerCase</code></td>
+<td>
+optional constant for lower case solution. </td></tr>
+<tr valign="top"><td><code>neighborRadius</code></td>
+<td>
+radius of the corresponding (unconditional)
+contamination neighborhood. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"ContIC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- ContIC()
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/ContNeighborhood-class.html
===================================================================
--- pkg/RobAStBase/chm/ContNeighborhood-class.html (rev 0)
+++ pkg/RobAStBase/chm/ContNeighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,93 @@
+<html><head><title>Contamination Neighborhood</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>ContNeighborhood-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: ContNeighborhood-class">
+<param name="keyword" value=" Contamination Neighborhood">
+</object>
+
+
+<h2>Contamination Neighborhood</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of (unconditional) contamination neighborhoods.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("ContNeighborhood", ...)</code>.
+More frequently they are created via the generating function
+<code>ContNeighborhood</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
+“(uncond.) convex contamination neighborhood”. </dd>
+
+
+<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
+neighborhood radius. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"UncondNeighborhood"</code>, directly.<br>
+Class <code>"Neighborhood"</code>, by class <code>"UncondNeighborhood"</code>.
+</p>
+
+
+<h3>Methods</h3>
+
+<p>
+No methods defined with class "ContNeighborhood" in the signature.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="ContNeighborhood.html">ContNeighborhood</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("ContNeighborhood")
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/ContNeighborhood.html
===================================================================
--- pkg/RobAStBase/chm/ContNeighborhood.html (rev 0)
+++ pkg/RobAStBase/chm/ContNeighborhood.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,81 @@
+<html><head><title>Generating function for ContNeighborhood-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>ContNeighborhood(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: ContNeighborhood">
+<param name="keyword" value=" Generating function for ContNeighborhood-class">
+</object>
+
+
+<h2>Generating function for ContNeighborhood-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"ContNeighborhood"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>ContNeighborhood(radius = 0)</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>radius</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"ContNeighborhood"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="ContNeighborhood-class.html">ContNeighborhood-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+ContNeighborhood()
+
+## The function is currently defined as
+function(radius = 0){
+ new("ContNeighborhood", radius = radius)
+}
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/FixRobModel-class.html
===================================================================
--- pkg/RobAStBase/chm/FixRobModel-class.html (rev 0)
+++ pkg/RobAStBase/chm/FixRobModel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,103 @@
+<html><head><title>Robust model with fixed (unconditional) neighborhood</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>FixRobModel-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: FixRobModel-class">
+<param name="keyword" value="R: neighbor<-,FixRobModel-method">
+<param name="keyword" value="R: show,FixRobModel-method">
+<param name="keyword" value=" Robust model with fixed (unconditional) neighborhood">
+</object>
+
+
+<h2>Robust model with fixed (unconditional) neighborhood</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of robust models with fixed (unconditional) neighborhoods.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("FixRobModel", ...)</code>.
+More frequently they are created via the generating function
+<code>FixRobModel</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>center</code>:</dt><dd>Object of class <code>"ProbFamily"</code>. </dd>
+<dt><code>neighbor</code>:</dt><dd>Object of class <code>"UncondNeighborhood"</code>.</dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"RobModel"</code>, directly.
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+<dt>neighbor<-</dt><dd><code>signature(object = "FixRobModel")</code>:
+replacement function for slot <code>neighbor<-</code> </dd>
+
+
+<dt>show</dt><dd><code>signature(object = "FixRobModel")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'ProbFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ProbFamily-class</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>,
+<code><a href="FixRobModel.html">FixRobModel</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("FixRobModel")
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/FixRobModel.html
===================================================================
--- pkg/RobAStBase/chm/FixRobModel.html (rev 0)
+++ pkg/RobAStBase/chm/FixRobModel.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,87 @@
+<html><head><title>Generating function for FixRobModel-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>FixRobModel(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: FixRobModel">
+<param name="keyword" value=" Generating function for FixRobModel-class">
+</object>
+
+
+<h2>Generating function for FixRobModel-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"FixRobModel"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+FixRobModel(center = ParamFamily(modifyParam =
+ function(theta) Norm(mean = theta)), neighbor = ContNeighborhood())
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>center</code></td>
+<td>
+object of class <code>"ProbFamily"</code> </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"UncondNeighborhood"</code> </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"FixRobModel"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="FixRobModel-class.html">FixRobModel-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+(M1 <- FixRobModel())
+
+## The function is currently defined as
+function(center = ParamFamily(), neighbor = ContNeighborhood()){
+ new("FixRobModel", center = center, neighbor = neighbor)
+}
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/IC-class.html
===================================================================
--- pkg/RobAStBase/chm/IC-class.html (rev 0)
+++ pkg/RobAStBase/chm/IC-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,154 @@
+<html><head><title>Influence curve</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>IC-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: IC-class">
+<param name="keyword" value="R: CallL2Fam">
+<param name="keyword" value="R: CallL2Fam,IC-method">
+<param name="keyword" value="R: CallL2Fam<-">
+<param name="keyword" value="R: CallL2Fam<-,IC-method">
+<param name="keyword" value="R: checkIC,IC,missing-method">
+<param name="keyword" value="R: checkIC,IC,L2ParamFamily-method">
+<param name="keyword" value="R: evalIC,IC,numeric-method">
+<param name="keyword" value="R: evalIC,IC,matrix-method">
+<param name="keyword" value="R: infoPlot,IC-method">
+<param name="keyword" value="R: plot,IC-method">
+<param name="keyword" value="R: show,IC-method">
+<param name="keyword" value=" Influence curve">
+</object>
+
+
+<h2>Influence curve</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of (partial) influence curves.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("IC", ...)</code>.
+More frequently they are created via the generating function
+<code>IC</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>CallL2Fam</code>:</dt><dd>Object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </dd>
+<dt><code>name</code>:</dt><dd>Object of class <code>"character"</code>. </dd>
+<dt><code>Curve</code>:</dt><dd>Object of class <code>"EuclRandVarList"</code>.</dd>
+<dt><code>Risks</code>:</dt><dd>Object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </dd>
+<dt><code>Infos</code>:</dt><dd>Object of class <code>"matrix"</code>
+with two columns named <code>method</code> and <code>message</code>:
+additional informations. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"InfluenceCurve"</code>, directly.
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+<dt>CallL2Fam</dt><dd><code>signature(object = "IC")</code>:
+accessor function for slot <code>CallL2Fam</code>. </dd>
+
+
+<dt>CallL2Fam<-</dt><dd><code>signature(object = "IC")</code>:
+replacement function for slot <code>CallL2Fam</code>. </dd>
+
+
+<dt>checkIC</dt><dd><code>signature(IC = "IC", L2Fam = "missing")</code>:
+check centering and Fisher consistency of <code>IC</code> assuming
+the L2-differentiable parametric family which can
+be generated via the slot <code>CallL2Fam</code> of <code>IC</code>. </dd>
+
+
+<dt>checkIC</dt><dd><code>signature(IC = "IC", L2Fam = "L2ParamFamily")</code>:
+check centering and Fisher consistency of <code>IC</code> assuming
+the L2-differentiable parametric family <code>L2Fam</code>. </dd>
+
+
+<dt>evalIC</dt><dd><code>signature(IC = "IC", x = "numeric")</code>:
+evaluate <code>IC</code> at <code>x</code>. </dd>
+
+
+<dt>evalIC</dt><dd><code>signature(IC = "IC", x = "matrix")</code>:
+evaluate <code>IC</code> at the rows of <code>x</code>. </dd>
+
+
+<dt>infoPlot</dt><dd><code>signature(object = "IC")</code>:
+Plot absolute and relative information of <code>IC</code>. </dd>
+
+
+<dt>plot</dt><dd><code>signature(x = "IC")</code></dd>
+
+
+<dt>show</dt><dd><code>signature(object = "IC")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Hampel et al. (1986) <EM>Robust Statistics</EM>.
+The Approach Based on Influence Functions. New York: Wiley.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>, <code><a href="IC.html">IC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- new("IC")
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/IC.html
===================================================================
--- pkg/RobAStBase/chm/IC.html (rev 0)
+++ pkg/RobAStBase/chm/IC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,124 @@
+<html><head><title>Generating function for IC-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>IC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: IC">
+<param name="keyword" value=" Generating function for IC-class">
+</object>
+
+
+<h2>Generating function for IC-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"IC"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+IC(name, Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x}),
+ Domain = Reals())),
+ Risks, Infos, CallL2Fam = call("L2ParamFamily"))
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>name</code></td>
+<td>
+Object of class <code>"character"</code>. </td></tr>
+<tr valign="top"><td><code>CallL2Fam</code></td>
+<td>
+object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </td></tr>
+<tr valign="top"><td><code>Curve</code></td>
+<td>
+object of class <code>"EuclRandVarList"</code>. </td></tr>
+<tr valign="top"><td><code>Risks</code></td>
+<td>
+object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </td></tr>
+<tr valign="top"><td><code>Infos</code></td>
+<td>
+matrix of characters with two columns
+named <code>method</code> and <code>message</code>: additional informations. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Hampel et al. (1986) <EM>Robust Statistics</EM>.
+The Approach Based on Influence Functions. New York: Wiley.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- IC()
+plot(IC1)
+
+## The function is currently defined as
+IC <- function(name, Curve = EuclRandVarList(RealRandVariable(Map = list(function(x){x})),
+ Domain = Reals()), Risks, Infos, CallL2Fam = call("L2ParamFamily")){
+ if(missing(name))
+ name <- "square integrable (partial) influence curve"
+ if(missing(Risks))
+ Risks <- list()
+ if(missing(Infos))
+ Infos <- matrix(c(character(0),character(0)), ncol=2,
+ dimnames=list(character(0), c("method", "message")))
+ return(new("IC", name = name, Curve = Curve, Risks = Risks,
+ Infos = Infos, CallL2Fam = CallL2Fam))
+}
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/InfRobModel-class.html
===================================================================
--- pkg/RobAStBase/chm/InfRobModel-class.html (rev 0)
+++ pkg/RobAStBase/chm/InfRobModel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,104 @@
+<html><head><title>Robust model with infinitesimal (unconditional) neighborhood</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>InfRobModel-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: InfRobModel-class">
+<param name="keyword" value="R: neighbor<-,InfRobModel-method">
+<param name="keyword" value="R: show,InfRobModel-method">
+<param name="keyword" value=" Robust model with infinitesimal (unconditional) neighborhood">
+</object>
+
+
+<h2>Robust model with infinitesimal (unconditional) neighborhood</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of robust models with infinitesimal (unconditional) neighborhoods;
+i.e., the neighborhood is shrinking at a rate of <i>sqrt(n)</i>.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("InfRobModel", ...)</code>.
+More frequently they are created via the generating function
+<code>InfRobModel</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>center</code>:</dt><dd>Object of class <code>"ProbFamily"</code>. </dd>
+<dt><code>neighbor</code>:</dt><dd>Object of class <code>"UncondNeighborhood"</code>. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"RobModel"</code>, directly.
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+<dt>neighbor<-</dt><dd><code>signature(object = "InfRobModel")</code>:
+replacement function for slot <code>neighbor<-</code> </dd>
+
+
+<dt>show</dt><dd><code>signature(object = "InfRobModel")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'ProbFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ProbFamily-class</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>,
+<code><a href="InfRobModel.html">InfRobModel</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("InfRobModel")
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/InfRobModel.html
===================================================================
--- pkg/RobAStBase/chm/InfRobModel.html (rev 0)
+++ pkg/RobAStBase/chm/InfRobModel.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,86 @@
+<html><head><title>Generating function for InfRobModel-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>InfRobModel(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: InfRobModel">
+<param name="keyword" value=" Generating function for InfRobModel-class">
+</object>
+
+
+<h2>Generating function for InfRobModel-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"InfRobModel"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+InfRobModel(center = L2ParamFamily(), neighbor = ContNeighborhood())
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>center</code></td>
+<td>
+object of class <code>"ProbFamily"</code> </td></tr>
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+object of class <code>"UncondNeighborhood"</code> </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"FixRobModel"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="RobModel-class.html">RobModel-class</a></code>, <code><a href="FixRobModel-class.html">FixRobModel-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+(M1 <- InfRobModel())
+
+## The function is currently defined as
+function(center = L2ParamFamily(), neighbor = ContNeighborhood()){
+ new("InfRobModel", center = center, neighbor = neighbor)
+}
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/InfluenceCurve-class.html
===================================================================
--- pkg/RobAStBase/chm/InfluenceCurve-class.html (rev 0)
+++ pkg/RobAStBase/chm/InfluenceCurve-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,166 @@
+<html><head><title>Influence curve</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>InfluenceCurve-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: InfluenceCurve-class">
+<param name="keyword" value="R: addInfo<-">
+<param name="keyword" value="R: addInfo<-,InfluenceCurve-method">
+<param name="keyword" value="R: addRisk<-">
+<param name="keyword" value="R: addRisk<-,InfluenceCurve-method">
+<param name="keyword" value="R: Curve">
+<param name="keyword" value="R: Curve,InfluenceCurve-method">
+<param name="keyword" value="R: Domain,InfluenceCurve-method">
+<param name="keyword" value="R: Infos">
+<param name="keyword" value="R: Infos,InfluenceCurve-method">
+<param name="keyword" value="R: Infos<-">
+<param name="keyword" value="R: Infos<-,InfluenceCurve-method">
+<param name="keyword" value="R: Map,InfluenceCurve-method">
+<param name="keyword" value="R: name,InfluenceCurve-method">
+<param name="keyword" value="R: name<-,InfluenceCurve-method">
+<param name="keyword" value="R: Range,InfluenceCurve-method">
+<param name="keyword" value="R: Risks">
+<param name="keyword" value="R: Risks,InfluenceCurve-method">
+<param name="keyword" value="R: Risks<-">
+<param name="keyword" value="R: Risks<-,InfluenceCurve-method">
+<param name="keyword" value="R: show,InfluenceCurve-method">
+<param name="keyword" value=" Influence curve">
+</object>
+
+
+<h2>Influence curve</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of influence curves (functions).
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("InfluenceCurve", ...)</code>.
+More frequently they are created via the generating function
+<code>InfluenceCurve</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>name</code>:</dt><dd>object of class <code>"character"</code> </dd>
+<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code> </dd>
+<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </dd>
+<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
+with two columns named <code>method</code> and <code>message</code>:
+additional informations. </dd>
+</dl>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>name</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>name</code>. </dd>
+
+
+<dt>name<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+replacement function for slot <code>name</code>. </dd>
+
+
+<dt>Curve</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>Curve</code>. </dd>
+
+
+<dt>Map</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>Map</code> of slot <code>Curve</code>. </dd>
+
+
+<dt>Domain</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>Domain</code> of slot <code>Curve</code>. </dd>
+
+
+<dt>Range</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>Range</code> of slot <code>Curve</code>. </dd>
+
+
+<dt>Infos</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>Infos</code>. </dd>
+
+
+<dt>Infos<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+replacement function for slot <code>Infos</code>. </dd>
+
+
+<dt>addInfo<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+function to add an information to slot <code>Infos</code>. </dd>
+
+
+<dt>Risks</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+accessor function for slot <code>Risks</code>. </dd>
+
+
+<dt>Risks<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+replacement function for slot <code>Risks</code>. </dd>
+
+
+<dt>addRisk<-</dt><dd><code>signature(object = "InfluenceCurve")</code>:
+function to add a risk to slot <code>Risks</code>. </dd>
+
+
+<dt>show</dt><dd><code>signature(object = "InfluenceCurve")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Hampel et al. (1986) <EM>Robust Statistics</EM>.
+The Approach Based on Influence Functions. New York: Wiley.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="InfluenceCurve.html">InfluenceCurve</a></code>, <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("InfluenceCurve")
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/InfluenceCurve.html
===================================================================
--- pkg/RobAStBase/chm/InfluenceCurve.html (rev 0)
+++ pkg/RobAStBase/chm/InfluenceCurve.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,108 @@
+<html><head><title>Generating function for InfluenceCurve-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>InfluenceCurve(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: InfluenceCurve">
+<param name="keyword" value=" Generating function for InfluenceCurve-class">
+</object>
+
+
+<h2>Generating function for InfluenceCurve-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"InfluenceCurve"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+InfluenceCurve(name, Curve = EuclRandVarList(EuclRandVariable(Domain = Reals())),
+ Risks, Infos)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>name</code></td>
+<td>
+character string: name of the influence curve </td></tr>
+<tr valign="top"><td><code>Curve</code></td>
+<td>
+object of class <code>"EuclRandVarList"</code> </td></tr>
+<tr valign="top"><td><code>Risks</code></td>
+<td>
+list of risks </td></tr>
+<tr valign="top"><td><code>Infos</code></td>
+<td>
+matrix of characters with two columns
+named <code>method</code> and <code>message</code>: additional informations </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"InfluenceCurve"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Hampel et al. (1986) <EM>Robust Statistics</EM>.
+The Approach Based on Influence Functions. New York: Wiley.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+InfluenceCurve()
+
+## The function is currently defined as
+InfluenceCurve <- function(name, Curve = EuclRandVarList(EuclRandVariable(Domain = Reals())),
+ Risks, Infos){
+ if(missing(name))
+ name <- "influence curve"
+ if(missing(Risks))
+ Risks <- list()
+ if(missing(Infos))
+ Infos <- matrix(c(character(0),character(0)), ncol=2,
+ dimnames=list(character(0), c("method", "message")))
+
+ return(new("InfluenceCurve", name = name, Curve = Curve,
+ Risks = Risks, Infos = Infos))
+}
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/Neighborhood-class.html
===================================================================
--- pkg/RobAStBase/chm/Neighborhood-class.html (rev 0)
+++ pkg/RobAStBase/chm/Neighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,90 @@
+<html><head><title>Neighborhood</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>Neighborhood-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: Neighborhood-class">
+<param name="keyword" value="R: radius">
+<param name="keyword" value="R: radius,Neighborhood-method">
+<param name="keyword" value="R: show,Neighborhood-method">
+<param name="keyword" value="R: type,Neighborhood-method">
+<param name="keyword" value=" Neighborhood">
+</object>
+
+
+<h2>Neighborhood</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of neighborhoods of families of probability measures.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+A virtual Class: No objects may be created from it.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
+type of the neighborhood. </dd>
+<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
+neighborhood radius. </dd>
+</dl>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>type</dt><dd><code>signature(object = "Neighborhood")</code>:
+accessor function for slot <code>type</code>. </dd>
+<dt>radius</dt><dd><code>signature(object = "Neighborhood")</code>:
+accessor function for slot <code>radius</code>. </dd>
+<dt>show</dt><dd><code>signature(object = "Neighborhood")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'ProbFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ProbFamily-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/Rchm.css
===================================================================
--- pkg/RobAStBase/chm/Rchm.css (rev 0)
+++ pkg/RobAStBase/chm/Rchm.css 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,31 @@
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+span.file{font-family: monospace}
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+span.samp{font-family: monospace}
Added: pkg/RobAStBase/chm/RobAStBase.chm
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Property changes on: pkg/RobAStBase/chm/RobAStBase.chm
___________________________________________________________________
Name: svn:mime-type
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Added: pkg/RobAStBase/chm/RobAStBase.hhp
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--- pkg/RobAStBase/chm/RobAStBase.hhp (rev 0)
+++ pkg/RobAStBase/chm/RobAStBase.hhp 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,39 @@
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+Contents file=RobAStBase.toc
+Compatibility=1.1 or later
+Compiled file=RobAStBase.chm
+Default topic=00Index.html
+Display compile progress=No
+Full-text search=Yes
+Full text search stop list file=..\..\..\gnuwin32\help\R.stp
+Title=R Help for package RobAStBase
+
+
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+ContIC.html
+ContNeighborhood-class.html
+ContNeighborhood.html
+FixRobModel-class.html
+FixRobModel.html
+IC-class.html
+IC.html
+InfRobModel-class.html
+InfRobModel.html
+InfluenceCurve-class.html
+InfluenceCurve.html
+Neighborhood-class.html
+RobModel-class.html
+TotalVarIC-class.html
+TotalVarIC.html
+TotalVarNeighborhood-class.html
+TotalVarNeighborhood.html
+UncondNeighborhood-class.html
+checkIC.html
+evalIC.html
+generateIC.html
+infoPlot.html
+locMEstimator.html
+oneStepEstimator.html
Added: pkg/RobAStBase/chm/RobAStBase.toc
===================================================================
--- pkg/RobAStBase/chm/RobAStBase.toc (rev 0)
+++ pkg/RobAStBase/chm/RobAStBase.toc 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,595 @@
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+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
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+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="addRisk<-">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="addRisk<-,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="CallL2Fam">
+<param name="Local" value="IC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="CallL2Fam,IC-method">
+<param name="Local" value="IC-class.html">
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+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="CallL2Fam<-">
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+<param name="Name" value="CallL2Fam<-,ContIC-method">
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+<param name="Name" value="cent">
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+<param name="Name" value="cent<-">
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+<param name="Name" value="center">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
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+<param name="Name" value="center,RobModel-method">
+<param name="Local" value="RobModel-class.html">
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+<param name="Name" value="checkIC">
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+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCase">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCase,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCase,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCase<-">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCase<-,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="lowerCase<-,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
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+<param name="Name" value="Map,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="name,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
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+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="name,RobModel-method">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="name<-,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighbor">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighbor,RobModel-method">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighbor<-">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighbor<-,FixRobModel-method">
+<param name="Local" value="FixRobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighbor<-,InfRobModel-method">
+<param name="Local" value="InfRobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighbor<-,RobModel-method">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Neighborhood-class">
+<param name="Local" value="Neighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighborRadius">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighborRadius,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighborRadius,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighborRadius<-">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighborRadius<-,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="neighborRadius<-,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="oneStepEstimator">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="oneStepEstimator,matrix,InfluenceCurve,list-method">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="oneStepEstimator,matrix,InfluenceCurve,numeric-method">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="oneStepEstimator,numeric,InfluenceCurve,list-method">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="oneStepEstimator,numeric,InfluenceCurve,numeric-method">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="oneStepEstimator-methods">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="plot,IC-method">
+<param name="Local" value="IC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="radius">
+<param name="Local" value="Neighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="radius,Neighborhood-method">
+<param name="Local" value="Neighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Range,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Risks">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Risks,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Risks<-">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Risks<-,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="RobModel-class">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,FixRobModel-method">
+<param name="Local" value="FixRobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,IC-method">
+<param name="Local" value="IC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,InfluenceCurve-method">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,InfRobModel-method">
+<param name="Local" value="InfRobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,Neighborhood-method">
+<param name="Local" value="Neighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="show,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="stand">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="stand,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="stand,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="stand<-">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="stand<-,ContIC-method">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="stand<-,TotalVarIC-method">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="TotalVarIC">
+<param name="Local" value="TotalVarIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="TotalVarIC-class">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="TotalVarNeighborhood">
+<param name="Local" value="TotalVarNeighborhood.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="TotalVarNeighborhood-class">
+<param name="Local" value="TotalVarNeighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="type,Neighborhood-method">
+<param name="Local" value="Neighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="UncondNeighborhood-class">
+<param name="Local" value="UncondNeighborhood-class.html">
+</OBJECT>
+</UL>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Package RobAStBase: Titles">
+</OBJECT>
+<UL>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Contamination Neighborhood">
+<param name="Local" value="ContNeighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for ContIC-class">
+<param name="Local" value="ContIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for ContNeighborhood-class">
+<param name="Local" value="ContNeighborhood.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for FixRobModel-class">
+<param name="Local" value="FixRobModel.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for IC-class">
+<param name="Local" value="IC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for InfluenceCurve-class">
+<param name="Local" value="InfluenceCurve.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for InfRobModel-class">
+<param name="Local" value="InfRobModel.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for TotalVarIC-class">
+<param name="Local" value="TotalVarIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generating function for TotalVarNeighborhood-class">
+<param name="Local" value="TotalVarNeighborhood.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic Function for Checking ICs">
+<param name="Local" value="checkIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic function for evaluating ICs">
+<param name="Local" value="evalIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic function for the computation of location M estimators">
+<param name="Local" value="locMEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic function for the computation of one-step estimators">
+<param name="Local" value="oneStepEstimator.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Generic function for the generation of influence curves">
+<param name="Local" value="generateIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Influence curve">
+<param name="Local" value="InfluenceCurve-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Influence curve of contamination type">
+<param name="Local" value="ContIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Influence curve of total variation type">
+<param name="Local" value="TotalVarIC-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Neighborhood">
+<param name="Local" value="Neighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Plot absolute and relative information">
+<param name="Local" value="infoPlot.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Robust model">
+<param name="Local" value="RobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Robust model with fixed (unconditional) neighborhood">
+<param name="Local" value="FixRobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Robust model with infinitesimal (unconditional) neighborhood">
+<param name="Local" value="InfRobModel-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Total variation neighborhood">
+<param name="Local" value="TotalVarNeighborhood-class.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Unconditional neighborhood">
+<param name="Local" value="UncondNeighborhood-class.html">
+</OBJECT>
+</UL>
+</UL>
+</BODY></HTML>
Added: pkg/RobAStBase/chm/RobModel-class.html
===================================================================
--- pkg/RobAStBase/chm/RobModel-class.html (rev 0)
+++ pkg/RobAStBase/chm/RobModel-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,98 @@
+<html><head><title>Robust model</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>RobModel-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: RobModel-class">
+<param name="keyword" value="R: center">
+<param name="keyword" value="R: center,RobModel-method">
+<param name="keyword" value="R: center<-">
+<param name="keyword" value="R: center<-,RobModel-method">
+<param name="keyword" value="R: name,RobModel-method">
+<param name="keyword" value="R: neighbor">
+<param name="keyword" value="R: neighbor,RobModel-method">
+<param name="keyword" value="R: neighbor<-">
+<param name="keyword" value="R: neighbor<-,RobModel-method">
+<param name="keyword" value=" Robust model">
+</object>
+
+
+<h2>Robust model</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of robust models. A robust model consists
+of family of probability measures <code>center</code> and a
+neighborhood <code>neighbor</code> about this family.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+A virtual Class: No objects may be created from it.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>center</code>:</dt><dd>Object of class <code>"ProbFamily"</code> </dd>
+<dt><code>neighbor</code>:</dt><dd>Object of class <code>"Neighborhood"</code></dd>
+</dl>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>center</dt><dd><code>signature(object = "RobModel")</code>:
+accessor function for slot <code>center</code>. </dd>
+<dt>center<-</dt><dd><code>signature(object = "RobModel")</code>:
+replacement function for slot <code>center</code>. </dd>
+<dt>neighbor</dt><dd><code>signature(object = "RobModel")</code>:
+accessor function for slot <code>neighbor</code>. </dd>
+<dt>neighbor<-</dt><dd><code>signature(object = "RobModel")</code>:
+replacement function for slot <code>neighbor</code>. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'ProbFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ProbFamily-class</a></code>, <code><a href="Neighborhood-class.html">Neighborhood-class</a></code>
+</p>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/TotalVarIC-class.html
===================================================================
--- pkg/RobAStBase/chm/TotalVarIC-class.html (rev 0)
+++ pkg/RobAStBase/chm/TotalVarIC-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,194 @@
+<html><head><title>Influence curve of total variation type</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>TotalVarIC-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: TotalVarIC-class">
+<param name="keyword" value="R: CallL2Fam<-,TotalVarIC-method">
+<param name="keyword" value="R: clipLo">
+<param name="keyword" value="R: clipLo,TotalVarIC-method">
+<param name="keyword" value="R: clipLo<-">
+<param name="keyword" value="R: clipLo<-,TotalVarIC-method">
+<param name="keyword" value="R: clipUp">
+<param name="keyword" value="R: clipUp,TotalVarIC-method">
+<param name="keyword" value="R: clipUp<-">
+<param name="keyword" value="R: clipUp<-,TotalVarIC-method">
+<param name="keyword" value="R: lowerCase,TotalVarIC-method">
+<param name="keyword" value="R: lowerCase<-,TotalVarIC-method">
+<param name="keyword" value="R: neighborRadius,TotalVarIC-method">
+<param name="keyword" value="R: neighborRadius<-,TotalVarIC-method">
+<param name="keyword" value="R: show,TotalVarIC-method">
+<param name="keyword" value="R: stand,TotalVarIC-method">
+<param name="keyword" value="R: stand<-,TotalVarIC-method">
+<param name="keyword" value="R: generateIC,TotalVarNeighborhood,L2ParamFamily-method">
+<param name="keyword" value=" Influence curve of total variation type">
+</object>
+
+
+<h2>Influence curve of total variation type</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of (partial) influence curves of total variation type.
+i.e., an influence curves <i>eta</i> of the form
+</p><p align="center"><i>eta = max(c, min(A Lambda, d))</i></p><p>
+with lower clipping bound <i>c</i>, upper clipping bound <i>d</i> and
+standardizing matrix <i>A</i>. <i>Lambda</i> stands for
+the L2 derivative of the corresponding L2 differentiable
+parametric family which can be created via <code>CallL2Fam</code>.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("TotalVarIC", ...)</code>.
+More frequently they are created via the generating function
+<code>TotalVarIC</code>, respectively via the method <code>generateIC</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>CallL2Fam</code>:</dt><dd>object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </dd>
+
+
+<dt><code>name</code>:</dt><dd>object of class <code>"character"</code>. </dd>
+
+
+<dt><code>Curve</code>:</dt><dd>object of class <code>"EuclRandVarList"</code>.</dd>
+
+
+<dt><code>Risks</code>:</dt><dd>object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </dd>
+
+
+<dt><code>Infos</code>:</dt><dd>object of class <code>"matrix"</code>
+with two columns named <code>method</code> and <code>message</code>:
+additional informations. </dd>
+
+
+<dt><code>clipLo</code>:</dt><dd>object of class <code>"numeric"</code>:
+lower clipping bound. </dd>
+
+
+<dt><code>clipUp</code>:</dt><dd>object of class <code>"numeric"</code>:
+upper clipping bound. </dd>
+
+
+<dt><code>stand</code>:</dt><dd>object of class <code>"matrix"</code>:
+standardizing matrix. </dd>
+
+
+<dt><code>neighborRadius</code>:</dt><dd>object of class <code>"numeric"</code>:
+radius of the corresponding (unconditional) contamination
+neighborhood. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"IC"</code>, directly.<br>
+Class <code>"InfluenceCurve"</code>, by class <code>"IC"</code>.
+</p>
+
+
+<h3>Methods</h3>
+
+<dl>
+<dt>CallL2Fam<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
+replacement function for slot <code>CallL2Fam</code>. </dd>
+
+
+<dt>clipLo</dt><dd><code>signature(object = "TotalVarIC")</code>:
+accessor function for slot <code>clipLo</code>. </dd>
+
+
+<dt>clipLo<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
+replacement function for slot <code>clipLo</code>. </dd>
+
+
+<dt>clipUp</dt><dd><code>signature(object = "TotalVarIC")</code>:
+accessor function for slot <code>clipUp</code>. </dd>
+
+
+<dt>clipUp<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
+replacement function for slot <code>clipUp</code>. </dd>
+
+
+<dt>stand</dt><dd><code>signature(object = "TotalVarIC")</code>:
+accessor function for slot <code>stand</code>. </dd>
+
+
+<dt>stand<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
+replacement function for slot <code>stand</code>. </dd>
+
+
+<dt>neighborRadius</dt><dd><code>signature(object = "TotalVarIC")</code>:
+accessor function for slot <code>neighborRadius</code>. </dd>
+
+
+<dt>neighborRadius<-</dt><dd><code>signature(object = "TotalVarIC")</code>:
+replacement function for slot <code>neighborRadius</code>. </dd>
+
+
+<dt>generateIC</dt><dd><code>signature(neighbor = "TotalVarNeighborhood", L2Fam = "L2ParamFamily")</code>:
+generate an object of class <code>"TotalVarIC"</code>. Rarely called directly. </dd>
+
+
+<dt>show</dt><dd><code>signature(object = "TotalVarIC")</code></dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- new("TotalVarIC")
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/TotalVarIC.html
===================================================================
--- pkg/RobAStBase/chm/TotalVarIC.html (rev 0)
+++ pkg/RobAStBase/chm/TotalVarIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,130 @@
+<html><head><title>Generating function for TotalVarIC-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>TotalVarIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: TotalVarIC">
+<param name="keyword" value=" Generating function for TotalVarIC-class">
+</object>
+
+
+<h2>Generating function for TotalVarIC-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"TotalVarIC"</code>;
+i.e., an influence curves <i>eta</i> of the form
+</p><p align="center"><i>eta = max(c, min(A Lambda, d))</i></p><p>
+with lower clipping bound <i>c</i>, upper clipping bound <i>d</i> and
+standardizing matrix <i>A</i>. <i>Lambda</i> stands for
+the L2 derivative of the corresponding L2 differentiable
+parametric family which can be created via <code>CallL2Fam</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+TotalVarIC(name, CallL2Fam = call("L2ParamFamily"),
+ Curve = EuclRandVarList(RealRandVariable(Map = c(function(x) {x}),
+ Domain = Reals())),
+ Risks, Infos, clipLo = -Inf, clipUp = Inf, stand = as.matrix(1),
+ lowerCase = NULL, neighborRadius = 0)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>name</code></td>
+<td>
+object of class <code>"character"</code>. </td></tr>
+<tr valign="top"><td><code>CallL2Fam</code></td>
+<td>
+object of class <code>"call"</code>:
+creates an object of the underlying L2-differentiable
+parametric family. </td></tr>
+<tr valign="top"><td><code>Curve</code></td>
+<td>
+object of class <code>"EuclRandVarList"</code>. </td></tr>
+<tr valign="top"><td><code>Risks</code></td>
+<td>
+object of class <code>"list"</code>:
+list of risks; cf. <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>. </td></tr>
+<tr valign="top"><td><code>Infos</code></td>
+<td>
+matrix of characters with two columns
+named <code>method</code> and <code>message</code>: additional informations. </td></tr>
+<tr valign="top"><td><code>clipLo</code></td>
+<td>
+negative real: lower clipping bound. </td></tr>
+<tr valign="top"><td><code>clipUp</code></td>
+<td>
+positive real: lower clipping bound. </td></tr>
+<tr valign="top"><td><code>stand</code></td>
+<td>
+matrix: standardizing matrix </td></tr>
+<tr valign="top"><td><code>lowerCase</code></td>
+<td>
+optional constant for lower case solution. </td></tr>
+<tr valign="top"><td><code>neighborRadius</code></td>
+<td>
+radius of the corresponding (unconditional)
+contamination neighborhood. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"TotalVarIC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC.html">ContIC</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- TotalVarIC()
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/TotalVarNeighborhood-class.html
===================================================================
--- pkg/RobAStBase/chm/TotalVarNeighborhood-class.html (rev 0)
+++ pkg/RobAStBase/chm/TotalVarNeighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,91 @@
+<html><head><title>Total variation neighborhood</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>TotalVarNeighborhood-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: TotalVarNeighborhood-class">
+<param name="keyword" value=" Total variation neighborhood">
+</object>
+
+
+<h2>Total variation neighborhood</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of (unconditional) total variation neighborhoods.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+Objects can be created by calls of the form <code>new("TotalVarNeighborhood", ...)</code>.
+More frequently they are created via the generating function
+<code>TotalVarNeighborhood</code>.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
+“(uncond.) total variation neighborhood”. </dd>
+<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
+neighborhood radius. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"UncondNeighborhood"</code>, directly.<br>
+Class <code>"Neighborhood"</code>, by class <code>"UncondNeighborhood"</code>.
+</p>
+
+
+<h3>Methods</h3>
+
+<p>
+No methods defined with class "TotalVarNeighborhood" in the signature.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="TotalVarNeighborhood.html">TotalVarNeighborhood</a></code>, <code><a href="UncondNeighborhood-class.html">UncondNeighborhood-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+new("TotalVarNeighborhood")
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/TotalVarNeighborhood.html
===================================================================
--- pkg/RobAStBase/chm/TotalVarNeighborhood.html (rev 0)
+++ pkg/RobAStBase/chm/TotalVarNeighborhood.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,81 @@
+<html><head><title>Generating function for TotalVarNeighborhood-class</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>TotalVarNeighborhood(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: TotalVarNeighborhood">
+<param name="keyword" value=" Generating function for TotalVarNeighborhood-class">
+</object>
+
+
+<h2>Generating function for TotalVarNeighborhood-class</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an object of class <code>"TotalVarNeighborhood"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>TotalVarNeighborhood(radius = 0)</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>radius</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"ContNeighborhood"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="TotalVarNeighborhood-class.html">TotalVarNeighborhood-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+TotalVarNeighborhood()
+
+## The function is currently defined as
+function(radius = 0){
+ new("TotalVarNeighborhood", radius = radius)
+}
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/UncondNeighborhood-class.html
===================================================================
--- pkg/RobAStBase/chm/UncondNeighborhood-class.html (rev 0)
+++ pkg/RobAStBase/chm/UncondNeighborhood-class.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,74 @@
+<html><head><title>Unconditional neighborhood</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>UncondNeighborhood-class(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: UncondNeighborhood-class">
+<param name="keyword" value=" Unconditional neighborhood">
+</object>
+
+
+<h2>Unconditional neighborhood</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Class of unconditonal (errors-in-variables) neighborhoods.
+</p>
+
+
+<h3>Objects from the Class</h3>
+
+<p>
+A virtual Class: No objects may be created from it.
+</p>
+
+
+<h3>Slots</h3>
+
+<dl>
+<dt><code>type</code>:</dt><dd>Object of class <code>"character"</code>:
+type of the neighborhood. </dd>
+<dt><code>radius</code>:</dt><dd>Object of class <code>"numeric"</code>:
+neighborhood radius. </dd>
+</dl>
+
+<h3>Extends</h3>
+
+<p>
+Class <code>"Neighborhood"</code>, directly.
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="Neighborhood-class.html">Neighborhood-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/checkIC.html
===================================================================
--- pkg/RobAStBase/chm/checkIC.html (rev 0)
+++ pkg/RobAStBase/chm/checkIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,103 @@
+<html><head><title>Generic Function for Checking ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>checkIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: checkIC">
+<param name="keyword" value=" Generic Function for Checking ICs">
+</object>
+
+
+<h2>Generic Function for Checking ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for checking centering and Fisher
+consistency of ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+checkIC(IC, L2Fam, ...)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"IC"</code> </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2-differentiable family of probability measures. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The precisions of the centering and the Fisher consistency
+are computed.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The maximum deviation from the IC properties is returned.</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'L2ParamFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">L2ParamFamily-class</a></code>, <code><a href="IC-class.html">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- new("IC")
+checkIC(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/evalIC.html
===================================================================
--- pkg/RobAStBase/chm/evalIC.html (rev 0)
+++ pkg/RobAStBase/chm/evalIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,83 @@
+<html><head><title>Generic function for evaluating ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>evalIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: evalIC">
+<param name="keyword" value=" Generic function for evaluating ICs">
+</object>
+
+
+<h2>Generic function for evaluating ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for evaluating ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+evalIC(IC, x)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"IC"</code> </td></tr>
+<tr valign="top"><td><code>x</code></td>
+<td>
+numeric vector or matrix </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The list of random variables contained in the slot <code>Curve</code>
+is evaluated at <code>x</code>.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+In case <code>x</code> is numeric a vector and in case <code>x</code>
+is matrix a matrix is returned.</p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/generateIC.html
===================================================================
--- pkg/RobAStBase/chm/generateIC.html (rev 0)
+++ pkg/RobAStBase/chm/generateIC.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,78 @@
+<html><head><title>Generic function for the generation of influence curves</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>generateIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: generateIC">
+<param name="keyword" value=" Generic function for the generation of influence curves">
+</object>
+
+
+<h2>Generic function for the generation of influence curves</h2>
+
+
+<h3>Description</h3>
+
+<p>
+This function is rarely called directly. It is used
+by other functions to create objects of class <code>"IC"</code>.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+generateIC(neighbor, L2Fam, ...)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>neighbor</code></td>
+<td>
+Object of class <code>"Neighborhood"</code>. </td></tr>
+<tr valign="top"><td><code>L2Fam</code></td>
+<td>
+L2-differentiable family of probability measures. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="IC-class.html">IC-class</a></code>, <code><a href="ContIC-class.html">ContIC-class</a></code>, <code><a href="TotalVarIC-class.html">TotalVarIC-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/infoPlot.html
===================================================================
--- pkg/RobAStBase/chm/infoPlot.html (rev 0)
+++ pkg/RobAStBase/chm/infoPlot.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,92 @@
+<html><head><title>Plot absolute and relative information</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>infoPlot(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: infoPlot">
+<param name="keyword" value=" Plot absolute and relative information">
+</object>
+
+
+<h2>Plot absolute and relative information</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Plot absolute and relative information of influence curves.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+infoPlot(object)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>object</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+Absolute information is defined as the square of the length
+of an IC. The relative information is defined as the
+absolute information of one component with respect to the
+absolute information of the whole IC; confer Section 8.1
+of Kohl (2005).
+</p>
+
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('distrMod', 'L2ParamFamily-class.html')" style="text-decoration: underline; color: blue; cursor: hand">L2ParamFamily-class</a></code>, <code><a href="IC-class.html">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+N <- NormLocationScaleFamily(mean=0, sd=1)
+IC1 <- optIC(model = N, risk = asCov())
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/locMEstimator.html
===================================================================
--- pkg/RobAStBase/chm/locMEstimator.html (rev 0)
+++ pkg/RobAStBase/chm/locMEstimator.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,101 @@
+<html><head><title>Generic function for the computation of location M estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>locMEstimator(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: locMEstimator">
+<param name="keyword" value="R: locMEstimator-methods">
+<param name="keyword" value="R: locMEstimator,numeric,InfluenceCurve-method">
+<param name="keyword" value=" Generic function for the computation of location M estimators">
+</object>
+
+
+<h2>Generic function for the computation of location M estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of location M estimators.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+locMEstimator(x, IC, ...)
+
+## S4 method for signature 'numeric, InfluenceCurve':
+locMEstimator(x, IC, eps = .Machine$double.eps^0.5)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>x</code></td>
+<td>
+sample </td></tr>
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters </td></tr>
+<tr valign="top"><td><code>eps</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Value</h3>
+
+<p>
+Returns a list with component
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>loc</code></td>
+<td>
+M estimator of location </td></tr>
+</table>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>x = "numeric", IC = "InfluenceCurve"</dt><dd>univariate location. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1964) Robust estimation of a location parameter.
+Ann. Math. Stat. <B>35</B>: 73–101.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobAStBase/chm/logo.jpg
===================================================================
(Binary files differ)
Property changes on: pkg/RobAStBase/chm/logo.jpg
___________________________________________________________________
Name: svn:mime-type
+ application/octet-stream
Added: pkg/RobAStBase/chm/oneStepEstimator.html
===================================================================
--- pkg/RobAStBase/chm/oneStepEstimator.html (rev 0)
+++ pkg/RobAStBase/chm/oneStepEstimator.html 2008-02-16 03:32:41 UTC (rev 25)
@@ -0,0 +1,100 @@
+<html><head><title>Generic function for the computation of one-step estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>oneStepEstimator(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: oneStepEstimator">
+<param name="keyword" value="R: oneStepEstimator-methods">
+<param name="keyword" value="R: oneStepEstimator,numeric,InfluenceCurve,numeric-method">
+<param name="keyword" value="R: oneStepEstimator,numeric,InfluenceCurve,list-method">
+<param name="keyword" value="R: oneStepEstimator,matrix,InfluenceCurve,numeric-method">
+<param name="keyword" value="R: oneStepEstimator,matrix,InfluenceCurve,list-method">
+<param name="keyword" value=" Generic function for the computation of one-step estimators">
+</object>
+
+
+<h2>Generic function for the computation of one-step estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of one-step estimators.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+oneStepEstimator(x, IC, start)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>x</code></td>
+<td>
+sample </td></tr>
+<tr valign="top"><td><code>IC</code></td>
+<td>
+object of class <code>"InfluenceCurve"</code> </td></tr>
+<tr valign="top"><td><code>start</code></td>
+<td>
+initial estimate </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+Given an initial estimation <code>start</code>, a sample <code>x</code>
+and an influence curve <code>IC</code> the corresponding one-step
+estimator is computed
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+The one-step estimation is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>x = "numeric", IC = "InfluenceCurve", start = "numeric"</dt><dd>univariate samples. </dd>
+<dt>x = "numeric", IC = "InfluenceCurve", start = "list"</dt><dd>univariate samples. </dd>
+<dt>x = "matrix", IC = "InfluenceCurve", start = "numeric"</dt><dd>multivariate samples. </dd>
+<dt>x = "matrix", IC = "InfluenceCurve", start = "list"</dt><dd>multivariate samples. </dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>
+</p>
+
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Modified: pkg/RobAStBase/man/ContIC-class.Rd
===================================================================
--- pkg/RobAStBase/man/ContIC-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/ContIC-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -50,7 +50,7 @@
\item{\code{Curve}:}{ object of class \code{"EuclRandVarList"}}
\item{\code{Risks}:}{ object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{\code{Infos}:}{ object of class \code{"matrix"}
with two columns named \code{method} and \code{message}:
Modified: pkg/RobAStBase/man/ContIC.Rd
===================================================================
--- pkg/RobAStBase/man/ContIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/ContIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -25,7 +25,7 @@
parametric family. }
\item{Curve}{ object of class \code{"EuclRandVarList"} }
\item{Risks}{ object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{Infos}{ matrix of characters with two columns
named \code{method} and \code{message}: additional informations. }
\item{clip}{ positive real: clipping bound. }
Modified: pkg/RobAStBase/man/FixRobModel-class.Rd
===================================================================
--- pkg/RobAStBase/man/FixRobModel-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/FixRobModel-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -36,7 +36,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{ProbFamily-class}}, \code{\link{UncondNeighborhood-class}},
+\seealso{\code{\link[distrMod]{ProbFamily-class}}, \code{\link{UncondNeighborhood-class}},
\code{\link{FixRobModel}}}
\examples{
new("FixRobModel")
Modified: pkg/RobAStBase/man/FixRobModel.Rd
===================================================================
--- pkg/RobAStBase/man/FixRobModel.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/FixRobModel.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -6,7 +6,8 @@
Generates an object of class \code{"FixRobModel"}.
}
\usage{
-FixRobModel(center = ParamFamily(), neighbor = ContNeighborhood())
+FixRobModel(center = ParamFamily(modifyParam =
+ function(theta) Norm(mean = theta)), neighbor = ContNeighborhood())
}
\arguments{
\item{center}{ object of class \code{"ProbFamily"} }
@@ -22,7 +23,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{FixRobModel-class}}}
+\seealso{\code{\link[RobAStBase]{FixRobModel-class}}}
\examples{
(M1 <- FixRobModel())
Modified: pkg/RobAStBase/man/IC-class.Rd
===================================================================
--- pkg/RobAStBase/man/IC-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/IC-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -28,7 +28,7 @@
\item{\code{name}:}{Object of class \code{"character"}. }
\item{\code{Curve}:}{Object of class \code{"EuclRandVarList"}.}
\item{\code{Risks}:}{Object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{\code{Infos}:}{Object of class \code{"matrix"}
with two columns named \code{method} and \code{message}:
additional informations. }
Modified: pkg/RobAStBase/man/IC.Rd
===================================================================
--- pkg/RobAStBase/man/IC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/IC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -17,7 +17,7 @@
parametric family. }
\item{Curve}{ object of class \code{"EuclRandVarList"}. }
\item{Risks}{ object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{Infos}{ matrix of characters with two columns
named \code{method} and \code{message}: additional informations. }
}
Modified: pkg/RobAStBase/man/InfRobModel-class.Rd
===================================================================
--- pkg/RobAStBase/man/InfRobModel-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/InfRobModel-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -37,7 +37,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{ProbFamily-class}}, \code{\link{UncondNeighborhood-class}},
+\seealso{\code{\link[distrMod]{ProbFamily-class}}, \code{\link{UncondNeighborhood-class}},
\code{\link{InfRobModel}}}
\examples{
new("InfRobModel")
Modified: pkg/RobAStBase/man/InfluenceCurve-class.Rd
===================================================================
--- pkg/RobAStBase/man/InfluenceCurve-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/InfluenceCurve-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -34,7 +34,7 @@
\item{\code{name}:}{ object of class \code{"character"} }
\item{\code{Curve}:}{ object of class \code{"EuclRandVarList"} }
\item{\code{Risks}:}{ object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{\code{Infos}:}{ object of class \code{"matrix"}
with two columns named \code{method} and \code{message}:
additional informations. }
@@ -92,7 +92,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{InfluenceCurve}}, \code{\link{RiskType-class}}}
+\seealso{\code{\link{InfluenceCurve}}, \code{\link[distrMod]{RiskType-class}}}
\examples{
new("InfluenceCurve")
}
Modified: pkg/RobAStBase/man/Neighborhood-class.Rd
===================================================================
--- pkg/RobAStBase/man/Neighborhood-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/Neighborhood-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -34,7 +34,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{ProbFamily-class}}}
+\seealso{\code{\link[distrMod]{ProbFamily-class}}}
%\examples{}
\concept{neighborhood}
\keyword{classes}
Modified: pkg/RobAStBase/man/RobModel-class.Rd
===================================================================
--- pkg/RobAStBase/man/RobModel-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/RobModel-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -42,7 +42,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{ProbFamily-class}}, \code{\link{Neighborhood-class}}}
+\seealso{\code{\link[distrMod]{ProbFamily-class}}, \code{\link{Neighborhood-class}}}
%\examples{}
\concept{robust model}
\keyword{classes}
Modified: pkg/RobAStBase/man/TotalVarIC-class.Rd
===================================================================
--- pkg/RobAStBase/man/TotalVarIC-class.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/TotalVarIC-class.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -44,7 +44,7 @@
\item{\code{Curve}:}{ object of class \code{"EuclRandVarList"}.}
\item{\code{Risks}:}{ object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{\code{Infos}:}{ object of class \code{"matrix"}
with two columns named \code{method} and \code{message}:
Modified: pkg/RobAStBase/man/TotalVarIC.Rd
===================================================================
--- pkg/RobAStBase/man/TotalVarIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/TotalVarIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -25,7 +25,7 @@
parametric family. }
\item{Curve}{ object of class \code{"EuclRandVarList"}. }
\item{Risks}{ object of class \code{"list"}:
- list of risks; cf. \code{\link{RiskType-class}}. }
+ list of risks; cf. \code{\link[distrMod]{RiskType-class}}. }
\item{Infos}{ matrix of characters with two columns
named \code{method} and \code{message}: additional informations. }
\item{clipLo}{ negative real: lower clipping bound. }
Modified: pkg/RobAStBase/man/checkIC.Rd
===================================================================
--- pkg/RobAStBase/man/checkIC.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/checkIC.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -27,7 +27,7 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{L2ParamFamily-class}}, \code{\link{IC-class}}}
+\seealso{\code{\link[distrMod]{L2ParamFamily-class}}, \code{\link{IC-class}}}
\examples{
IC1 <- new("IC")
checkIC(IC1)
Modified: pkg/RobAStBase/man/infoPlot.Rd
===================================================================
--- pkg/RobAStBase/man/infoPlot.Rd 2008-02-15 14:58:30 UTC (rev 24)
+++ pkg/RobAStBase/man/infoPlot.Rd 2008-02-16 03:32:41 UTC (rev 25)
@@ -25,9 +25,10 @@
}
\author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
%\note{}
-\seealso{\code{\link{L2ParamFamily-class}}, \code{\link{IC-class}}}
+\seealso{\code{\link[distrMod]{L2ParamFamily-class}}, \code{\link{IC-class}}}
\examples{
N <- NormLocationScaleFamily(mean=0, sd=1)
+## require(ROptEst)
IC1 <- optIC(model = N, risk = asCov())
infoPlot(IC1)
}
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