[Robast-commits] r148 - in branches/robast-0.6/pkg/ROptEst: R inst/scripts man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Thu Aug 7 05:40:33 CEST 2008


Author: stamats
Date: 2008-08-07 05:40:33 +0200 (Thu, 07 Aug 2008)
New Revision: 148

Modified:
   branches/robast-0.6/pkg/ROptEst/R/roptest.R
   branches/robast-0.6/pkg/ROptEst/inst/scripts/PoissonModel.R
   branches/robast-0.6/pkg/ROptEst/man/getAsRisk.Rd
   branches/robast-0.6/pkg/ROptEst/man/getBiasIC.Rd
   branches/robast-0.6/pkg/ROptEst/man/getInfCent.Rd
   branches/robast-0.6/pkg/ROptEst/man/getInfClip.Rd
   branches/robast-0.6/pkg/ROptEst/man/getInfRobIC.Rd
   branches/robast-0.6/pkg/ROptEst/man/getInfStand.Rd
   branches/robast-0.6/pkg/ROptEst/man/getL1normL2deriv.Rd
   branches/robast-0.6/pkg/ROptEst/man/leastFavorableRadius.Rd
   branches/robast-0.6/pkg/ROptEst/man/minmaxBias.Rd
   branches/robast-0.6/pkg/ROptEst/man/optIC.Rd
   branches/robast-0.6/pkg/ROptEst/man/roptest.Rd
Log:
correction of several documentation errors, adaption to new implementation of ParamFamily and MCEstimator

Modified: branches/robast-0.6/pkg/ROptEst/R/roptest.R
===================================================================
--- branches/robast-0.6/pkg/ROptEst/R/roptest.R	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/R/roptest.R	2008-08-07 03:40:33 UTC (rev 148)
@@ -3,7 +3,7 @@
 ###############################################################################
 roptest <- function(x, L2Fam, eps, eps.lower, eps.upper, initial.est, 
                     neighbor = ContNeighborhood(), risk = asMSE(), steps = 1, 
-                    distance = CvMDist, interval, par, verbose = FALSE, 
+                    distance = CvMDist, startPar = NULL, verbose = FALSE, 
                     useLast = getRobAStBaseOption("kStepUseLast"), ...){
     es.call <- match.call()
     if(missing(x))
@@ -52,7 +52,7 @@
 
     if(missing(initial.est)){
         initial.est <- estimate(MDEstimator(x = x, ParamFamily = L2Fam, distance = distance,
-                                            interval = interval, par = par, ...))
+                                            startPar = startPar, ...))
     }
     newParam <- param(L2Fam)
     main(newParam) <- initial.est

Modified: branches/robast-0.6/pkg/ROptEst/inst/scripts/PoissonModel.R
===================================================================
--- branches/robast-0.6/pkg/ROptEst/inst/scripts/PoissonModel.R	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/inst/scripts/PoissonModel.R	2008-08-07 03:40:33 UTC (rev 148)
@@ -127,17 +127,17 @@
 (est0 <- mean(x))
 
 ## with distrMod
-MLEstimator(x, PoisFamily(), interval = c(0, 10))
+MLEstimator(x, PoisFamily())
 
 ## with MASS
 library(MASS)
 fitdistr(x, densfun = "Poisson")
 
 ## 1.1. Kolmogorov(-Smirnov) minimum distance estimator
-(est11 <- MDEstimator(x=x, PoisFamily(), interval = c(0, 10)))
+(est11 <- MDEstimator(x=x, PoisFamily()))
 
 ## 1.2. Cramer von Mises minimum distance estimator
-(est12 <- MDEstimator(x=x, PoisFamily(), distance = CvMDist, interval = c(0, 10)))
+(est12 <- MDEstimator(x=x, PoisFamily(), distance = CvMDist))
 
 ## 2. k-step estimation: contamination neighborhood
 ## 2.1 small amount of contamination < 2%

Modified: branches/robast-0.6/pkg/ROptEst/man/getAsRisk.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getAsRisk.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getAsRisk.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -25,35 +25,49 @@
 \usage{
 getAsRisk(risk, L2deriv, neighbor, biastype, ...)
 
-\S4method{getAsRisk}{asMSE,UnivariateDistribution,Neighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asMSE,UnivariateDistribution,Neighborhood,ANY}(risk, L2deriv, 
+                                      neighbor, biastype, clip, cent, stand, trafo)
 
-\S4method{getAsRisk}{asMSE,EuclRandVariable,Neighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asMSE,EuclRandVariable,Neighborhood,ANY}(risk, L2deriv, neighbor, 
+                                                    biastype, clip, cent, stand, trafo)
 
-\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,ANY}(risk, L2deriv, 
+                                                              neighbor, biastype, trafo)
 
-\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,onesidedBias}(risk, L2deriv, neighbor, biastype, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,onesidedBias}(risk, 
+                                                      L2deriv, neighbor, biastype, trafo)
 
-\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias}(risk, L2deriv, neighbor, biastype, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,ContNeighborhood,asymmetricBias}(risk, 
+                                                        L2deriv, neighbor, biastype, trafo)
 
-\S4method{getAsRisk}{asBias,UnivariateDistribution,TotalVarNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, trafo)
+\S4method{getAsRisk}{asBias,UnivariateDistribution,TotalVarNeighborhood,ANY}(risk, L2deriv, 
+                                                                  neighbor, biastype, trafo)
 
-\S4method{getAsRisk}{asBias,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, trafo, z.start, A.start, maxiter, tol, warn)
+\S4method{getAsRisk}{asBias,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, 
+                              biastype, Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, 
+                              trafo, z.start, A.start, maxiter, tol, warn)
 
-\S4method{getAsRisk}{asCov,UnivariateDistribution,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+\S4method{getAsRisk}{asCov,UnivariateDistribution,ContNeighborhood,ANY}(risk, L2deriv, 
+                                                  neighbor, biastype, clip, cent, stand)
 
-\S4method{getAsRisk}{asCov,UnivariateDistribution,TotalVarNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+\S4method{getAsRisk}{asCov,UnivariateDistribution,TotalVarNeighborhood,ANY}(risk, L2deriv, 
+                                                    neighbor, biastype, clip, cent, stand)
 
-\S4method{getAsRisk}{asCov,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand)
+\S4method{getAsRisk}{asCov,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, 
+                           biastype, Distr, clip, cent, stand, 
+                           V.comp =  matrix(TRUE, ncol = nrow(stand), nrow = nrow(stand)), w)
 
-\S4method{getAsRisk}{trAsCov,UnivariateDistribution,UncondNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand)
+\S4method{getAsRisk}{trAsCov,UnivariateDistribution,UncondNeighborhood,ANY}(risk, L2deriv, 
+                                                      neighbor, biastype, clip, cent, stand)
 
-\S4method{getAsRisk}{trAsCov,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, Distr, clip, cent, stand, normtype)
+\S4method{getAsRisk}{trAsCov,RealRandVariable,ContNeighborhood,ANY}(risk, L2deriv, neighbor, 
+                                                biastype, Distr, clip, cent, stand, normtype)
 
-\S4method{getAsRisk}{asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY}(risk, L2deriv, neighbor, biastype, clip, cent, stand, trafo)
+\S4method{getAsRisk}{asUnOvShoot,UnivariateDistribution,UncondNeighborhood,ANY}(risk, L2deriv, 
+                                                  neighbor, biastype, clip, cent, stand, trafo)
 
-\S4method{getAsRisk}{asSemivar,UnivariateDistribution,Neighborhood,onesidedBias}(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"}. }
@@ -76,6 +90,9 @@
   \item{tol}{ the desired accuracy (convergence tolerance).}
   \item{warn}{ logical: print warnings. }
   \item{normtype}{ object of class \code{"NormType"}. }
+  \item{V.comp}{ matrix: indication which components of the standardizing
+    matrix have to be computed. }
+  \item{w}{object of class \code{RobWeight}; current weight}  
 }
 \details{ This function is rarely called directly. It is used by 
   other functions/methods. }

Modified: branches/robast-0.6/pkg/ROptEst/man/getBiasIC.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getBiasIC.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getBiasIC.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -11,7 +11,7 @@
 \usage{
 getBiasIC(IC, neighbor, ...)
 
-\S4method{getBiasIC}{HampIC,UncondNeighborhood}(IC, neighbor, L2Fam)
+\S4method{getBiasIC}{HampIC,UncondNeighborhood}(IC, neighbor, L2Fam, ...)
 }
 \arguments{
   \item{IC}{ object of class \code{"InfluenceCurve"} }

Modified: branches/robast-0.6/pkg/ROptEst/man/getInfCent.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getInfCent.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getInfCent.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -25,7 +25,7 @@
      neighbor, biastype, clip, cent, tol.z, symm, trafo)
 
 \S4method{getInfCent}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, 
-     neighbor, biastype, z.comp, stand, cent, clip, w)
+     neighbor, biastype, Distr, z.comp, w)
 
 \S4method{getInfCent}{UnivariateDistribution,ContNeighborhood,onesidedBias}(L2deriv, 
      neighbor, biastype, clip, cent, tol.z, symm, trafo)
@@ -41,10 +41,10 @@
   \item{\dots}{ additional parameters. }
   \item{clip}{ optimal clipping bound. }
   \item{cent}{ optimal centering constant. }
-  \item{stand}{ standardizing matrix. }
   \item{tol.z}{ the desired accuracy (convergence tolerance). }
   \item{symm}{ logical: indicating symmetry of \code{L2deriv}. }
   \item{trafo}{ matrix: transformation of the parameter. }
+  \item{Distr}{object of class \code{Distribution}. }
   \item{z.comp}{ logical vector: indication which components of the 
     centering constant have to be computed. }
   \item{w}{object of class \code{RobWeight}; current weight}  

Modified: branches/robast-0.6/pkg/ROptEst/man/getInfClip.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getInfClip.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getInfClip.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -16,15 +16,20 @@
 \usage{
 getInfClip(clip, L2deriv, risk, neighbor, ...)
 
-\S4method{getInfClip}{numeric,UnivariateDistribution,asMSE,ContNeighborhood}(clip, L2deriv, risk, neighbor, biastype, 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, biastype, 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, biastype, cent, trafo)
+\S4method{getInfClip}{numeric,EuclRandVariable,asMSE,ContNeighborhood}(clip, L2deriv, risk, 
+                                              neighbor, biastype, Distr, stand, cent, trafo)
 
-\S4method{getInfClip}{numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(clip, L2deriv, risk, neighbor, biastype, 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, cent, symm, trafo)
+\S4method{getInfClip}{numeric,UnivariateDistribution,asSemivar,ContNeighborhood}(clip, L2deriv, 
+                                                              risk, neighbor, cent, symm, trafo)
 }
 \arguments{
   \item{clip}{ positive real: clipping bound }

Modified: branches/robast-0.6/pkg/ROptEst/man/getInfRobIC.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getInfRobIC.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getInfRobIC.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -29,22 +29,22 @@
                        QuadForm = diag(nrow(trafo)), verbose = FALSE)
 
 \S4method{getInfRobIC}{UnivariateDistribution,asBias,UncondNeighborhood}(L2deriv, risk, neighbor, symm, trafo, 
-             maxiter, tol, warn, Finfo, verbose = FALSE)
+             maxiter, tol, warn, Finfo, verbose = FALSE, ...)
 
 \S4method{getInfRobIC}{RealRandVariable,asBias,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, z.start, A.start, Finfo, trafo, maxiter, tol, warn, verbose = FALSE)
+             L2derivDistrSymm, z.start, A.start, Finfo, trafo, maxiter, tol, warn, verbose = FALSE, ...)
 
 \S4method{getInfRobIC}{UnivariateDistribution,asHampel,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo, 
              upper, maxiter, tol, warn, noLow = FALSE, verbose = FALSE)
 
 \S4method{getInfRobIC}{RealRandVariable,asHampel,ContNeighborhood}(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn, verbose = FALSE)
+             L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start, A.start, upper, maxiter, tol, warn, verbose = FALSE)
 
 \S4method{getInfRobIC}{UnivariateDistribution,asGRisk,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo, 
              upper, maxiter, tol, warn, noLow = FALSE, verbose = FALSE)
 
 \S4method{getInfRobIC}{RealRandVariable,asGRisk,ContNeighborhood}(L2deriv, risk, neighbor,  Distr, DistrSymm, L2derivSymm, 
-             L2derivDistrSymm, Finfo, z.start, A.start, trafo, onesetLM = FALSE, upper, maxiter, tol, warn, verbose = FALSE)
+             L2derivDistrSymm, Finfo, trafo, onesetLM = FALSE, z.start, A.start, upper, maxiter, tol, warn, verbose = FALSE)
 
 \S4method{getInfRobIC}{UnivariateDistribution,asUnOvShoot,UncondNeighborhood}(L2deriv, risk, neighbor, symm, Finfo, trafo, 
              upper, maxiter, tol, warn)

Modified: branches/robast-0.6/pkg/ROptEst/man/getInfStand.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getInfStand.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getInfStand.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -23,7 +23,7 @@
      neighbor, biastype, clip, cent, trafo)
 
 \S4method{getInfStand}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, 
-     neighbor, biastype, Distr, A.comp, stand, clip, cent, trafo, w)
+     neighbor, biastype, Distr, A.comp, cent, trafo, w)
 
 \S4method{getInfStand}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv, 
      neighbor, biastype, clip, cent, trafo)
@@ -39,7 +39,6 @@
   \item{\dots}{ additional parameters }
   \item{clip}{ optimal clipping bound. }
   \item{cent}{ optimal centering constant. }
-  \item{stand}{ standardizing matrix. }
   \item{Distr}{ object of class \code{"Distribution"}. }
   \item{trafo}{ matrix: transformation of the parameter. }  
   \item{A.comp}{ matrix: indication which components of the standardizing

Modified: branches/robast-0.6/pkg/ROptEst/man/getL1normL2deriv.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/getL1normL2deriv.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/getL1normL2deriv.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -12,9 +12,8 @@
 \S4method{getL1normL2deriv}{UnivariateDistribution}(L2deriv, 
      cent, ...)
 
-\S4method{getL1normL2deriv}{UnivariateDistribution}(L2deriv, 
+\S4method{getL1normL2deriv}{RealRandVariable}(L2deriv, 
      cent, stand, Distr, normtype, ...)
-
 }
 %\details{}
 \arguments{

Modified: branches/robast-0.6/pkg/ROptEst/man/leastFavorableRadius.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/leastFavorableRadius.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/leastFavorableRadius.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -13,7 +13,7 @@
 \S4method{leastFavorableRadius}{L2ParamFamily,UncondNeighborhood,asGRisk}(
           L2Fam, neighbor, risk, rho, upRad = 1, 
             z.start = NULL, A.start = NULL, upper = 100, maxiter = 100, 
-            tol = .Machine$double.eps^0.4, warn = FALSE)
+            tol = .Machine$double.eps^0.4, warn = FALSE, verbose = FALSE)
 }
 \arguments{
   \item{L2Fam}{ L2-differentiable family of probability measures. }
@@ -29,6 +29,7 @@
   \item{maxiter}{ the maximum number of iterations }
   \item{tol}{ the desired accuracy (convergence tolerance).}
   \item{warn}{ logical: print warnings. }
+  \item{verbose}{ logical: if \code{TRUE}, some messages are printed }
 }
 %\details{}
 \value{

Modified: branches/robast-0.6/pkg/ROptEst/man/minmaxBias.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/minmaxBias.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/minmaxBias.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -17,7 +17,7 @@
 minmaxBias(L2deriv, neighbor, biastype, ...)
 
 \S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype, symm, trafo, 
-             maxiter, tol, Finfo)
+             maxiter, tol, warn, Finfo)
 
 \S4method{minmaxBias}{UnivariateDistribution,ContNeighborhood,asymmetricBias}(L2deriv, neighbor, biastype, symm, trafo, 
              maxiter, tol, warn, Finfo)
@@ -28,8 +28,8 @@
 \S4method{minmaxBias}{UnivariateDistribution,TotalVarNeighborhood,BiasType}(L2deriv, neighbor, biastype, symm, trafo, 
              maxiter, tol, warn, Finfo)
 
-\S4method{minmaxBias}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype, Distr, 
-             L2derivDistrSymm, z.start, A.start,  z.comp, A.comp, trafo, maxiter, tol, warn)
+\S4method{minmaxBias}{RealRandVariable,ContNeighborhood,BiasType}(L2deriv, neighbor, biastype, normtype, Distr, 
+             z.start, A.start,  z.comp, A.comp, trafo, maxiter, tol)
 
 }
 \arguments{
@@ -37,10 +37,10 @@
     of probability measures. }
   \item{neighbor}{ object of class \code{"Neighborhood"}. }
   \item{biastype}{ object of class \code{"BiasType"}. }
+  \item{normtype}{ object of class \code{"NormType"}. }
   \item{\dots}{ additional parameters. }
   \item{Distr}{ object of class \code{"Distribution"}. }
   \item{symm}{ logical: indicating symmetry of \code{L2deriv}. }
-  \item{L2derivDistrSymm}{ object of class \code{"DistrSymmList"}. }
   \item{z.start}{ initial value for the centering constant. }
   \item{A.start}{ initial value for the standardizing matrix. }
   \item{z.comp}{ \code{logical} indicator which indices need to be computed and which are 0 due to symmetry. }

Modified: branches/robast-0.6/pkg/ROptEst/man/optIC.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/optIC.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/optIC.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -22,7 +22,8 @@
 
 \S4method{optIC}{FixRobModel,fiUnOvShoot}(model, risk, sampleSize, upper = 1e4, 
                                           maxiter = 50, tol = .Machine$double.eps^0.4, 
-                                          warn = TRUE, Algo = "A", cont = "left")
+                                          warn = TRUE, Algo = "A", cont = "left",
+                                          verbose = FALSE)
 }
 \arguments{
   \item{model}{ probability model. }

Modified: branches/robast-0.6/pkg/ROptEst/man/roptest.Rd
===================================================================
--- branches/robast-0.6/pkg/ROptEst/man/roptest.Rd	2008-08-06 13:42:14 UTC (rev 147)
+++ branches/robast-0.6/pkg/ROptEst/man/roptest.Rd	2008-08-07 03:40:33 UTC (rev 148)
@@ -8,7 +8,7 @@
 \usage{
 roptest(x, L2Fam, eps, eps.lower, eps.upper, initial.est, 
         neighbor = ContNeighborhood(), risk = asMSE(), steps = 1, 
-        distance = CvMDist, interval, par, verbose = FALSE, 
+        distance = CvMDist, startPar = NULL, verbose = FALSE, 
         useLast = getRobAStBaseOption("kStepUseLast"), ...)
 }
 \arguments{
@@ -26,9 +26,12 @@
   \item{risk}{ object of class \code{"RiskType"} }
   \item{steps}{ positive integer: number of steps used for k-steps construction }
   \item{distance}{ distance function }
-  \item{interval}{ parameter interval for univariate parameters }
-  \item{par}{ initial parameter value for multivariate parameters.
-        If missing, the parameters of \code{L2Fam} are used. }
+  \item{startPar}{ initial information used by \code{optimize} resp. \code{optim};
+    i.e; if (total) parameter is of length 1, \code{startPar} is 
+    a search interval, else it is an initial parameter value; if \code{NULL}
+    slot \code{startPar} of \code{ParamFamily} is used to produce it;
+    in the multivariate case, \code{startPar} may also be of class \code{Estimate},
+    in which case slot \code{untransformed.estimate} is used.}
   \item{verbose}{ logical: if \code{TRUE}, some messages are printed }
   \item{useLast}{ which parameter estimate (initial estimate or
     k-step estimate) shall be used to fill the slots \code{pIC},
@@ -108,13 +111,13 @@
 x <- rbinom(100, size=25, prob=(1-ind)*0.25 + ind*0.9)
 
 ## ML-estimate
-MLEstimator(x, BinomFamily(size = 25), interval = c(0, 1))
+MLEstimator(x, BinomFamily(size = 25))
 
 ## compute optimally robust estimator (known contamination)
-roptest(x, BinomFamily(size = 25), eps = 0.05, interval = c(0, 1), steps = 3)
+roptest(x, BinomFamily(size = 25), eps = 0.05, steps = 3)
 
 ## compute optimally robust estimator (unknown contamination)
-roptest(x, BinomFamily(size = 25), eps.lower = 0, eps.upper = 0.1, interval = c(0, 1), steps = 3)
+roptest(x, BinomFamily(size = 25), eps.lower = 0, eps.upper = 0.1, steps = 3)
 
 
 #############################
@@ -126,10 +129,10 @@
        rep(10, 10), rep(11, 4), rep(12, 0), rep(13, 1), rep(14, 1))
 
 ## ML-estimate
-MLEstimator(x, PoisFamily(), interval = c(0, 10))
+MLEstimator(x, PoisFamily())
 
 ## compute optimally robust estimator (unknown contamination)
-roptest(x, PoisFamily(), eps.upper = 0.05, interval = c(0, 10), steps = 3)
+roptest(x, PoisFamily(), eps.upper = 0.05, steps = 3)
 
 #############################
 ## 3. Normal (Gaussian) location and scale



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