[Robast-commits] r577 - in branches/robast-0.9/pkg/RobLox: . R inst inst/scripts man tests/Examples

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Tue Jan 29 09:28:42 CET 2013


Author: stamats
Date: 2013-01-29 09:28:41 +0100 (Tue, 29 Jan 2013)
New Revision: 577

Added:
   branches/robast-0.9/pkg/RobLox/R/ZZZinternal.R
   branches/robast-0.9/pkg/RobLox/chm/
Modified:
   branches/robast-0.9/pkg/RobLox/DESCRIPTION
   branches/robast-0.9/pkg/RobLox/R/sysdata.rda
   branches/robast-0.9/pkg/RobLox/inst/NEWS
   branches/robast-0.9/pkg/RobLox/inst/scripts/LMinterpolation.R
   branches/robast-0.9/pkg/RobLox/man/0RobLox-package.Rd
   branches/robast-0.9/pkg/RobLox/man/rlsOptIC.AL.Rd
   branches/robast-0.9/pkg/RobLox/man/rlsOptIC.An1.Rd
   branches/robast-0.9/pkg/RobLox/man/rlsOptIC.Ha3.Rd
   branches/robast-0.9/pkg/RobLox/man/roblox.Rd
   branches/robast-0.9/pkg/RobLox/man/rowRoblox.Rd
   branches/robast-0.9/pkg/RobLox/man/showdown.Rd
   branches/robast-0.9/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save
Log:
merged trunk into branch, update of Rout.save, had to put several examples in \dontrun to reduce check time

Modified: branches/robast-0.9/pkg/RobLox/DESCRIPTION
===================================================================
--- branches/robast-0.9/pkg/RobLox/DESCRIPTION	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/DESCRIPTION	2013-01-29 08:28:41 UTC (rev 577)
@@ -1,6 +1,6 @@
 Package: RobLox
 Version: 0.9
-Date: 2012-07-01
+Date: 2013-01-29
 Title: Optimally robust influence curves and estimators for location and scale
 Description: Functions for the determination of optimally robust influence curves and
         estimators in case of normal location and/or scale
@@ -15,4 +15,4 @@
 URL: http://robast.r-forge.r-project.org/
 LastChangedDate: {$LastChangedDate$}
 LastChangedRevision: {$LastChangedRevision$}
-SVNRevision: 454
+SVNRevision: 519

Copied: branches/robast-0.9/pkg/RobLox/R/ZZZinternal.R (from rev 576, pkg/RobLox/R/ZZZinternal.R)
===================================================================
--- branches/robast-0.9/pkg/RobLox/R/ZZZinternal.R	                        (rev 0)
+++ branches/robast-0.9/pkg/RobLox/R/ZZZinternal.R	2013-01-29 08:28:41 UTC (rev 577)
@@ -0,0 +1,34 @@
+## due to a change to .C in 2.16.0
+## location
+.getA.loc <- function(r){
+    approx(x = .radius.gitter, y = .A.loc, xout = r, yleft = 1)$y
+}
+.getb.loc <- function(r){
+    approx(x = .radius.gitter, y = .b.loc, xout = r, yleft = Inf)$y
+}
+
+## scale
+.getA.sc <- function(r){
+    approx(x = .radius.gitter, y = .A.sc, xout = r, yleft = 0.5)$y
+}
+.geta.sc <- function(r){
+    approx(x = .radius.gitter, y = .a.sc, xout = r, yleft = 0)$y
+}
+.getb.sc <- function(r){
+    approx(x = .radius.gitter, y = .b.sc, xout = r, yleft = Inf)$y
+}
+
+## location and scale
+.getA1.locsc <- function(r){
+    approx(x = .radius.gitter, y = .A1.locsc, xout = r, yleft = 1)$y
+}
+.getA2.locsc <- function(r){
+    approx(x = .radius.gitter, y = .A2.locsc, xout = r, yleft = 0.5)$y
+}
+.geta.locsc <- function(r){
+    approx(x = .radius.gitter, y = .a.locsc, xout = r, yleft = 0)$y
+}
+.getb.locsc <- function(r){
+    approx(x = .radius.gitter, y = .b.locsc, xout = r, yleft = Inf)$y
+}
+

Modified: branches/robast-0.9/pkg/RobLox/R/sysdata.rda
===================================================================
(Binary files differ)

Modified: branches/robast-0.9/pkg/RobLox/inst/NEWS
===================================================================
--- branches/robast-0.9/pkg/RobLox/inst/NEWS	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/inst/NEWS	2013-01-29 08:28:41 UTC (rev 577)
@@ -8,6 +8,12 @@
  information)
 
 #######################################
+version 0.8.1
+#######################################
++ new internal functions due to changes to .C() and .Call() calls
+
+
+#######################################
 version 0.8
 #######################################
 

Modified: branches/robast-0.9/pkg/RobLox/inst/scripts/LMinterpolation.R
===================================================================
--- branches/robast-0.9/pkg/RobLox/inst/scripts/LMinterpolation.R	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/inst/scripts/LMinterpolation.R	2013-01-29 08:28:41 UTC (rev 577)
@@ -1,5 +1,8 @@
 ###############################################################################
 ## Interpolated functions to speed up computation of Lagrange Multipliers
+## 
+## regarding a change to .C calls and approxfun in R 2.16.0, we need to make
+## distinction between version before 2.16.0 and afterwards
 ###############################################################################
 
 library(RobLox)
@@ -15,28 +18,26 @@
 locationScale <- sapply(radius, fun)
 #locationScale <- sapply(radius, rlsOptIC.AL, computeIC = FALSE)
 
-A.loc <- unlist(location[1,])
-b.loc <- unlist(location[3,])
-.getA.loc <- approxfun(radius, A.loc, yleft = 1)
-.getb.loc <- approxfun(radius, b.loc, yleft = Inf)
+## location
+.A.loc <- unlist(location[1,])
+.b.loc <- unlist(location[3,])
 
-A.sc <- unlist(scale[1,])
-a.sc <- unlist(scale[2,])
-b.sc <- unlist(scale[3,])
-.getA.sc <- approxfun(radius, A.sc, yleft = 0.5)
-.geta.sc <- approxfun(radius, a.sc, yleft = 0)
-.getb.sc <- approxfun(radius, b.sc, yleft = Inf)
+## scale
+.A.sc <- unlist(scale[1,])
+.a.sc <- unlist(scale[2,])
+.b.sc <- unlist(scale[3,])
 
+## location and scale
 n <- length(radius)
-A1.locsc <- unlist(locationScale[1,])[seq(1, 4*n-3, by = 4)]
-A2.locsc <- unlist(locationScale[1,])[seq(4, 4*n, by = 4)]
-a.locsc <- unlist(locationScale[2,])[seq(2, 2*n, by = 2)]
-b.locsc <- unlist(locationScale[3,])
-.getA1.locsc <- approxfun(radius, A1.locsc, yleft = 1)
-.getA2.locsc <- approxfun(radius, A2.locsc, yleft = 0.5)
-.geta.locsc <- approxfun(radius, a.locsc, yleft = 0)
-.getb.locsc <- approxfun(radius, b.locsc, yleft = Inf)
+.A1.locsc <- unlist(locationScale[1,])[seq(1, 4*n-3, by = 4)]
+.A2.locsc <- unlist(locationScale[1,])[seq(4, 4*n, by = 4)]
+.a.locsc <- unlist(locationScale[2,])[seq(2, 2*n, by = 2)]
+.b.locsc <- unlist(locationScale[3,])
 
-save(.getA.loc, .getb.loc, .getA.sc, .geta.sc, .getb.sc, .getA1.locsc, .getA2.locsc,
-     .geta.locsc, .getb.locsc, file = "savedata.rda")
+.radius.gitter <- radius
 
+## Saving the results in sysdata.rda
+#load("sysdata.rda")
+save(.radius.gitter, .finiteSampleRadius.loc, .finiteSampleRadius.locsc, .finiteSampleRadius.sc,
+     .A.loc, .b.loc, .A.sc, .a.sc, .b.sc, .A1.locsc, .A2.locsc, .a.locsc, .b.locsc,
+     file = "sysdata.rda")

Modified: branches/robast-0.9/pkg/RobLox/man/0RobLox-package.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/0RobLox-package.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/0RobLox-package.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -12,13 +12,15 @@
 \details{
 \tabular{ll}{
 Package: \tab RobLox \cr
-Version: \tab 0.9 \cr
-Date: \tab 2012-07-1 \cr
-Depends: \tab R(>= 2.7.0), stats, distrMod(>= 2.0.1), RobAStBase(>= 0.1.1) \cr
+Version: \tab 0.8.2 \cr
+Date: \tab 2012-09-12 \cr
+Depends: \tab R(>= 2.7.0), stats, lattice, RColorBrewer, Biobase, distr, distrMod, RobAStBase\cr
+Suggests: \tab MASS\cr
 LazyLoad: \tab yes \cr
+ByteCompile: \tab yes \cr
 License: \tab LGPL-3 \cr
 URL: \tab http://robast.r-forge.r-project.org/\cr
-SVNRevision: \tab 439 \cr
+SVNRevision: \tab 519 \cr
 }
 }
 \author{Matthias Kohl  \email{matthias.kohl at stamats.de}}
@@ -28,9 +30,13 @@
 
   Rieder, H. (1994) \emph{Robust Asymptotic Statistics}. New York: Springer.
 
-  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. (2008). The Costs of not Knowing
+  the Radius. \emph{Statistical Methods and Applications} \bold{17}(1) 13-40.
   Extended version: \url{http://www.stamats.de/RRlong.pdf}
+  
+  M. Kohl, P. Ruckdeschel, and H. Rieder (2010). Infinitesimally Robust Estimation 
+  in General Smoothly Parametrized Models. \emph{Statistical Methods and Application}, 
+  \bold{19}(3):333-354. 
 }
 \seealso{ \code{\link[RobAStBase:0RobAStBase-package]{RobAStBase-package}} }
 \section{Package versions}{
@@ -50,11 +56,15 @@
 confint(res)
 confint(res, method = symmetricBias())
 pIC(res)
+
+## don't run to reduce check time on CRAN
+\dontrun{
 checkIC(pIC(res))
 Risks(pIC(res))
 Infos(pIC(res))
 plot(pIC(res))
 infoPlot(pIC(res))
+}
 
 ## row-wise application
 ind <- rbinom(200, size=1, prob=0.05) 

Modified: branches/robast-0.9/pkg/RobLox/man/rlsOptIC.AL.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/rlsOptIC.AL.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/rlsOptIC.AL.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -60,6 +60,9 @@
 cent(IC1)
 clip(IC1)
 stand(IC1)
+
+## don't run to reduce check time on CRAN
+\dontrun{
 plot(IC1)
 infoPlot(IC1)
 
@@ -97,6 +100,7 @@
 ## choose k = 3
 (est4 <- kStepEstimator(x, IC2, est0, steps = 3L))
 }
+}
 \concept{normal location and scale}
 \concept{influence curve}
 \keyword{robust}

Modified: branches/robast-0.9/pkg/RobLox/man/rlsOptIC.An1.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/rlsOptIC.An1.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/rlsOptIC.An1.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -35,9 +35,12 @@
 checkIC(IC1)
 Risks(IC1)
 Infos(IC1)
+## don't run to reduce check time on CRAN
+\dontrun{
 plot(IC1)
 infoPlot(IC1)
 }
+}
 \concept{normal location and scale}
 \concept{influence curve}
 \keyword{robust}

Modified: branches/robast-0.9/pkg/RobLox/man/rlsOptIC.Ha3.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/rlsOptIC.Ha3.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/rlsOptIC.Ha3.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -40,9 +40,12 @@
 checkIC(IC1)
 Risks(IC1)
 Infos(IC1)
+## don't run to reduce check time on CRAN
+\dontrun{
 plot(IC1)
 infoPlot(IC1)
 }
+}
 \concept{normal location and scale}
 \concept{influence curve}
 \keyword{robust}

Modified: branches/robast-0.9/pkg/RobLox/man/roblox.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/roblox.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/roblox.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -78,6 +78,10 @@
   Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
   the Radius. Statistical Methods and Applications \emph{17}(1) 13-40.
   Extended version: \url{http://www.stamats.de/RRlong.pdf}
+  
+  M. Kohl, P. Ruckdeschel, and H. Rieder (2010). Infinitesimally Robust Estimation 
+  in General Smoothly Parametrized Models. \emph{Statistical Methods and Application}, 
+  \bold{19}(3):333-354. 
 }
 \author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
 %\note{}
@@ -92,6 +96,8 @@
 ## amount of gross errors known
 res1 <- roblox(x, eps = 0.05, returnIC = TRUE)
 estimate(res1)
+## don't run to reduce check time on CRAN
+\dontrun{
 confint(res1)
 confint(res1, method = symmetricBias())
 pIC(res1)
@@ -100,10 +106,13 @@
 Infos(pIC(res1))
 plot(pIC(res1))
 infoPlot(pIC(res1))
+}
 
 ## amount of gross errors unknown
 res2 <- roblox(x, eps.lower = 0.01, eps.upper = 0.1, returnIC = TRUE)
 estimate(res2)
+## don't run to reduce check time on CRAN
+\dontrun{
 confint(res2)
 confint(res2, method = symmetricBias())
 pIC(res2)
@@ -112,6 +121,7 @@
 Infos(pIC(res2))
 plot(pIC(res2))
 infoPlot(pIC(res2))
+}
 
 ## estimator comparison
 # classical optimal (non-robust)

Modified: branches/robast-0.9/pkg/RobLox/man/rowRoblox.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/rowRoblox.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/rowRoblox.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -88,6 +88,10 @@
   Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
   the Radius. Statistical Methods and Applications \emph{17}(1) 13-40.
   Extended version: \url{http://www.stamats.de/RRlong.pdf}
+  
+  M. Kohl, P. Ruckdeschel, and H. Rieder (2010). Infinitesimally Robust Estimation 
+  in General Smoothly Parametrized Models. \emph{Statistical Methods and Application}, 
+  \bold{19}(3):333-354. 
 }
 \author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
 %\note{}

Modified: branches/robast-0.9/pkg/RobLox/man/showdown.Rd
===================================================================
--- branches/robast-0.9/pkg/RobLox/man/showdown.Rd	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/man/showdown.Rd	2013-01-29 08:28:41 UTC (rev 577)
@@ -58,6 +58,10 @@
   Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
   the Radius. Statistical Methods and Applications \emph{17}(1) 13-40.
   Extended version: \url{http://www.stamats.de/RRlong.pdf}
+  
+  M. Kohl, P. Ruckdeschel, and H. Rieder (2010). Infinitesimally Robust Estimation 
+  in General Smoothly Parametrized Models. \emph{Statistical Methods and Application}, 
+  \bold{19}(3):333-354. 
 }
 \author{Matthias Kohl \email{Matthias.Kohl at stamats.de}}
 %\note{}

Modified: branches/robast-0.9/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save
===================================================================
--- branches/robast-0.9/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save	2013-01-29 04:34:41 UTC (rev 576)
+++ branches/robast-0.9/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save	2013-01-29 08:28:41 UTC (rev 577)
@@ -1,6 +1,6 @@
 
-R version 2.15.1 Patched (2012-06-29 r59688) -- "Roasted Marshmallows"
-Copyright (C) 2012 The R Foundation for Statistical Computing
+R Under development (unstable) (2013-01-26 r61749) -- "Unsuffered Consequences"
+Copyright (C) 2013 The R Foundation for Statistical Computing
 ISBN 3-900051-07-0
 Platform: x86_64-unknown-linux-gnu (64-bit)
 
@@ -26,19 +26,27 @@
 Loading required package: RColorBrewer
 Loading required package: Biobase
 Loading required package: BiocGenerics
+Loading required package: parallel
 
 Attaching package: ‘BiocGenerics’
 
-The following object(s) are masked from ‘package:stats’:
+The following objects are masked from ‘package:parallel’:
 
+    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
+    clusterExport, clusterMap, parApply, parCapply, parLapply,
+    parLapplyLB, parRapply, parSapply, parSapplyLB
+
+The following object is masked from ‘package:stats’:
+
     xtabs
 
-The following object(s) are masked from ‘package:base’:
+The following objects are masked from ‘package:base’:
 
-    Filter, Find, Map, Position, Reduce, anyDuplicated, cbind,
-    colnames, duplicated, eval, get, intersect, lapply, mapply, mget,
-    order, paste, pmax, pmax.int, pmin, pmin.int, rbind, rep.int,
-    rownames, sapply, setdiff, table, tapply, union, unique
+    Filter, Find, Map, Position, Reduce, anyDuplicated, as.data.frame,
+    cbind, colnames, duplicated, eval, get, intersect, lapply, mapply,
+    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
+    rbind, rep.int, rownames, sapply, setdiff, sort, table, tapply,
+    union, unique, unlist
 
 Welcome to Bioconductor
 
@@ -58,6 +66,13 @@
 :SweaveListingUtils>  Utilities for Sweave together with
 :SweaveListingUtils>  TeX listings package (version 0.6)
 :SweaveListingUtils> 
+:SweaveListingUtils>  NOTE: Support for this package
+:SweaveListingUtils>  will stop soon.
+:SweaveListingUtils> 
+:SweaveListingUtils>  Package 'knitr' is providing the
+:SweaveListingUtils>  same functionality in a better
+:SweaveListingUtils>  way.
+:SweaveListingUtils> 
 :SweaveListingUtils>  Some functions from package 'base'
 :SweaveListingUtils>  are intentionally masked ---see
 :SweaveListingUtils>  SweaveListingMASK().
@@ -77,7 +92,7 @@
 
 Attaching package: ‘SweaveListingUtils’
 
-The following object(s) are masked from ‘package:base’:
+The following object is masked from ‘package:base’:
 
     library, require
 
@@ -103,7 +118,7 @@
 
 Attaching package: ‘distr’
 
-The following object(s) are masked from ‘package:stats’:
+The following object is masked from ‘package:stats’:
 
     df, qqplot, sd
 
@@ -128,7 +143,7 @@
 
 Attaching package: ‘distrEx’
 
-The following object(s) are masked from ‘package:stats’:
+The following object is masked from ‘package:stats’:
 
     IQR, mad, median, var
 
@@ -165,19 +180,25 @@
 
 Attaching package: ‘distrMod’
 
-The following object(s) are masked from ‘package:stats4’:
+The following object is masked from ‘package:stats4’:
 
     confint
 
-The following object(s) are masked from ‘package:stats’:
+The following object is masked from ‘package:stats’:
 
     confint
 
-The following object(s) are masked from ‘package:base’:
+The following object is masked from ‘package:base’:
 
     norm
 
 Loading required package: RobAStBase
+Loading required package: rrcov
+Loading required package: robustbase
+Loading required package: pcaPP
+Loading required package: mvtnorm
+Scalable Robust Estimators with High Breakdown Point (version 1.3-02)
+
 :RobAStBase>  Robust Asymptotic Statistics (version 0.9)
 :RobAStBase> 
 :RobAStBase>  Some functions from pkg's 'stats' and 'graphics'
@@ -193,18 +214,29 @@
 
 Attaching package: ‘RobAStBase’
 
-The following object(s) are masked from ‘package:graphics’:
+The following object is masked from ‘package:graphics’:
 
     clip
 
 > 
 > assign(".oldSearch", search(), pos = 'CheckExEnv')
+> assign(".ExTimings", "RobLox-Ex.timings", pos = 'CheckExEnv')
+> cat("name\tuser\tsystem\telapsed\n", file=get(".ExTimings", pos = 'CheckExEnv'))
+> assign(".format_ptime",
++ function(x) {
++   if(!is.na(x[4L])) x[1L] <- x[1L] + x[4L]
++   if(!is.na(x[5L])) x[2L] <- x[2L] + x[5L]
++   format(x[1L:3L])
++ },
++ pos = 'CheckExEnv')
+> 
 > cleanEx()
 > nameEx("0RobLox-package")
 > ### * 0RobLox-package
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: RobLox-package
 > ### Title: Optimally robust influence curves and estimators for location
 > ###   and scale
@@ -276,8 +308,8 @@
 ### L2-differentiable parametric family:	 normal location and scale family 
 ### param:	An object of class "ParamWithScaleFamParameter"
 name:	location and scale
-mean:	-0.111150435088002
-sd:	0.89284240215757
+mean:	-0.111150435088066
+sd:	0.892842402157418
 trafo:
      mean sd
 mean    1  0
@@ -301,41 +333,16 @@
 [1,] "finite-sample corrected radius-minimax estimate for contamination interval [0.01, 0.1]"
 [2,] "least favorable (uncorrected) contamination: 0.043"                                    
 [3,] "maximum asymptotic MSE-inefficiency: 1.441"                                            
-> checkIC(pIC(res))
-precision of centering:	 8.833545e-17 1.265596e-05 
-precision of Fisher consistency:
-             mean            sd
-mean 1.652391e-05 -1.822532e-17
-sd   3.168531e-17 -8.653862e-07
-maximum deviation 
-     1.652391e-05 
-> Risks(pIC(res))
-$asMSE
-[1] 2.385308
-
-$asBias
-[1] 1.679196
-
-$trAsCov
-[1] 1.546146
-
-$asCov
-          [,1]      [,2]
-[1,] 0.9947437 0.0000000
-[2,] 0.0000000 0.5514425
-
-> Infos(pIC(res))
-     method  
-[1,] "roblox"
-[2,] "roblox"
-[3,] "roblox"
-     message                                                                                 
-[1,] "finite-sample corrected radius-minimax estimate for contamination interval [0.01, 0.1]"
-[2,] "least favorable (uncorrected) contamination: 0.043"                                    
-[3,] "maximum asymptotic MSE-inefficiency: 1.441"                                            
-> plot(pIC(res))
-> infoPlot(pIC(res))
 > 
+> ## don't run to reduce check time on CRAN
+> ## Not run: 
+> ##D checkIC(pIC(res))
+> ##D Risks(pIC(res))
+> ##D Infos(pIC(res))
+> ##D plot(pIC(res))
+> ##D infoPlot(pIC(res))
+> ## End(Not run)
+> 
 > ## row-wise application
 > ind <- rbinom(200, size=1, prob=0.05) 
 > X <- matrix(rnorm(200, mean=ind*3, sd=(1-ind) + ind*9), nrow = 2)
@@ -362,12 +369,16 @@
 > 
 > 
 > 
+> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
+> cat("0RobLox-package", get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
 > cleanEx()
 > nameEx("finiteSampleCorrection")
 > ### * finiteSampleCorrection
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: finiteSampleCorrection
 > ### Title: Function to compute finite-sample corrected radii
 > ### Aliases: finiteSampleCorrection
@@ -384,12 +395,16 @@
 > 
 > 
 > 
+> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
+> cat("finiteSampleCorrection", get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
 > cleanEx()
 > nameEx("rlOptIC")
 > ### * rlOptIC
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: rlOptIC
 > ### Title: Computation of the optimally robust IC for AL estimators
 > ### Aliases: rlOptIC
@@ -425,15 +440,20 @@
          [,1]
 [1,] 1.054162
 > plot(IC1)
+NULL
 > 
 > 
 > 
+> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
+> cat("rlOptIC", get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
 > cleanEx()
 > nameEx("rlsOptIC.AL")
 > ### * rlsOptIC.AL
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: rlsOptIC.AL
 > ### Title: Computation of the optimally robust IC for AL estimators
 > ### Aliases: rlsOptIC.AL
@@ -479,295 +499,59 @@
         [,1]      [,2]
 [1,] 1.05189 0.0000000
 [2,] 0.00000 0.5958748
-> plot(IC1)
-> infoPlot(IC1)
 > 
-> ## k-step estimation
-> ## better use function roblox (see ?roblox)
-> ## 1. data: random sample
-> ind <- rbinom(100, size=1, prob=0.05) 
-> x <- rnorm(100, mean=0, sd=(1-ind) + ind*9)
-> mean(x)
-[1] 0.07372327
-> sd(x)
-[1] 1.642883
-> median(x)
-[1] -0.1176227
-> mad(x)
-[1] 0.7942541
+> ## don't run to reduce check time on CRAN
+> ## Not run: 
+> ##D plot(IC1)
+> ##D infoPlot(IC1)
+> ##D 
+> ##D ## k-step estimation
+> ##D ## better use function roblox (see ?roblox)
+> ##D ## 1. data: random sample
+> ##D ind <- rbinom(100, size=1, prob=0.05) 
+> ##D x <- rnorm(100, mean=0, sd=(1-ind) + ind*9)
+> ##D mean(x)
+> ##D sd(x)
+> ##D median(x)
+> ##D mad(x)
+> ##D 
+> ##D ## 2. Kolmogorov(-Smirnov) minimum distance estimator (default)
+> ##D ## -> we use it as initial estimate for one-step construction
+> ##D (est0 <- MDEstimator(x, ParamFamily = NormLocationScaleFamily()))
+> ##D 
+> ##D ## 3.1 one-step estimation: radius known
+> ##D IC1 <- rlsOptIC.AL(r = 0.5, mean = estimate(est0)[1], sd = estimate(est0)[2])
+> ##D (est1 <- oneStepEstimator(x, IC1, est0))
+> ##D 
+> ##D ## 3.2 k-step estimation: radius known
+> ##D ## Choose k = 3
+> ##D (est2 <- kStepEstimator(x, IC1, est0, steps = 3L))
+> ##D 
+> ##D ## 4.1 one-step estimation: radius unknown
+> ##D ## take least favorable radius r = 0.579
+> ##D ## cf. Table 8.1 in Kohl(2005)
+> ##D IC2 <- rlsOptIC.AL(r = 0.579, mean = estimate(est0)[1], sd = estimate(est0)[2])
+> ##D (est3 <- oneStepEstimator(x, IC2, est0))
+> ##D 
+> ##D ## 4.2 k-step estimation: radius unknown
+> ##D ## take least favorable radius r = 0.579
+> ##D ## cf. Table 8.1 in Kohl(2005)
+> ##D ## choose k = 3
+> ##D (est4 <- kStepEstimator(x, IC2, est0, steps = 3L))
+> ## End(Not run)
 > 
-> ## 2. Kolmogorov(-Smirnov) minimum distance estimator (default)
-> ## -> we use it as initial estimate for one-step construction
-> (est0 <- MDEstimator(x, ParamFamily = NormLocationScaleFamily()))
-Evaluations of Minimum Kolmogorov distance estimate:
-----------------------------------------------------
-An object of class “Estimate” 
-generated by call
-  MDEstimator(x = x, ParamFamily = NormLocationScaleFamily())
-samplesize:   100
-estimate:
-       mean          sd 
--0.05297991  0.92479741 
-Criterion:
-Kolmogorov distance 
-         0.05524875 
 > 
-> ## 3.1 one-step estimation: radius known
-> IC1 <- rlsOptIC.AL(r = 0.5, mean = estimate(est0)[1], sd = estimate(est0)[2])
-> (est1 <- oneStepEstimator(x, IC1, est0))
-Evaluations of 1-step estimate:
--------------------------------
-An object of class “Estimate” 
-generated by call
-  oneStepEstimator(x = x, IC = IC1, start = est0)
-samplesize:   100
-estimate:
-      mean           sd     
-  -0.11387679    0.94042674 
- ( 0.10700894) ( 0.09077496)
-asymptotic (co)variance (multiplied with samplesize):
-         [,1]      [,2]
-[1,] 1.145091 0.0000000
-[2,] 0.000000 0.8240093
-Infos:
-     method            
-[1,] "oneStepEstimator"
-[2,] "oneStepEstimator"
-     message                                                        
-[1,] "1-step estimate for normal location and scale family"         
-[2,] "computation of IC, trafo, asvar and asbias via useLast = TRUE"
-asymptotic bias:
-       sd 
-0.9036978 
-(partial) influence curve:
-An object of class “ContIC” 
-### name:	 IC of contamination type 
-
-### L2-differentiable parametric family:	 normal location and scale family 
-### param:	An object of class "ParamWithScaleFamParameter"
-name:	location and scale
-mean:	-0.113876786446744
-sd:	0.940426740646572
-trafo:
-     mean sd
-mean    1  0
-sd      0  1
-
-### neighborhood radius:	 0.5 
-
-### clip:	      sd 
-1.807396 
-### cent:	[1]  0.0000000 -0.3473252
-### stand:
-         [,1]     [,2]
-[1,] 1.402111 0.000000
-[2,] 0.000000 1.092111
-
-### Infos:
-  method     message                                            
-  "rlOptIC"  "optimally robust IC for AL estimators and 'asMSE'"
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-steps:
-[1] 1
 > 
-> ## 3.2 k-step estimation: radius known
-> ## Choose k = 3
-> (est2 <- kStepEstimator(x, IC1, est0, steps = 3L))
-Evaluations of 3-step estimate:
--------------------------------
-An object of class “Estimate” 
-generated by call
-  kStepEstimator(x = x, IC = IC1, start = est0, steps = 3L)
-samplesize:   100
-estimate:
-      mean           sd     
-  -0.11639567    0.93647284 
- ( 0.10655904) ( 0.09039331)
-asymptotic (co)variance (multiplied with samplesize):
-         [,1]     [,2]
-[1,] 1.135483 0.000000
-[2,] 0.000000 0.817095
-Infos:
-     method          
-[1,] "kStepEstimator"
-[2,] "kStepEstimator"
-     message                                                        
-[1,] "3-step estimate for normal location and scale family"         
-[2,] "computation of IC, trafo, asvar and asbias via useLast = TRUE"
-asymptotic bias:
-       sd 
-0.8998983 
-(partial) influence curve:
-An object of class “ContIC” 
-### name:	 IC of contamination type 
-
-### L2-differentiable parametric family:	 normal location and scale family 
-### param:	An object of class "ParamWithScaleFamParameter"
-name:	location and scale
-mean:	-0.116395665238717
-sd:	0.936472837098548
-trafo:
-     mean sd
-mean    1  0
-sd      0  1
-
-### neighborhood radius:	 0.5 
-
-### clip:	      sd 
-1.799797 
-### cent:	[1]  0.0000000 -0.3458649
-### stand:
-         [,1]     [,2]
-[1,] 1.390346 0.000000
-[2,] 0.000000 1.082947
-
-### Infos:
-  method     message                                            
-  "rlOptIC"  "optimally robust IC for AL estimators and 'asMSE'"
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-steps:
-[1] 3
 > 
-> ## 4.1 one-step estimation: radius unknown
-> ## take least favorable radius r = 0.579
-> ## cf. Table 8.1 in Kohl(2005)
-> IC2 <- rlsOptIC.AL(r = 0.579, mean = estimate(est0)[1], sd = estimate(est0)[2])
-> (est3 <- oneStepEstimator(x, IC2, est0))
-Evaluations of 1-step estimate:
--------------------------------
-An object of class “Estimate” 
-generated by call
-  oneStepEstimator(x = x, IC = IC2, start = est0)
-samplesize:   100
-estimate:
-      mean           sd     
-  -0.11948046    0.93188234 
- ( 0.10902521) ( 0.09686132)
-asymptotic (co)variance (multiplied with samplesize):
-        [,1]      [,2]
-[1,] 1.18865 0.0000000
-[2,] 0.00000 0.9382114
-Infos:
-     method            
-[1,] "oneStepEstimator"
-[2,] "oneStepEstimator"
-     message                                                        
-[1,] "1-step estimate for normal location and scale family"         
-[2,] "computation of IC, trafo, asvar and asbias via useLast = TRUE"
-asymptotic bias:
-      sd 
-1.000462 
-(partial) influence curve:
-An object of class “ContIC” 
-### name:	 IC of contamination type 
-
-### L2-differentiable parametric family:	 normal location and scale family 
-### param:	An object of class "ParamWithScaleFamParameter"
-name:	location and scale
-mean:	-0.119480464646407
-sd:	0.931882340990481
-trafo:
-     mean sd
-mean    1  0
-sd      0  1
-
-### neighborhood radius:	 0.579 
-
-### clip:	      sd 
-1.727914 
-### cent:	[1]  0.0000000 -0.4415319
-### stand:
-         [,1]     [,2]
-[1,] 1.505582 0.000000
-[2,] 0.000000 1.206776
-
-### Infos:
-  method     message                                            
-  "rlOptIC"  "optimally robust IC for AL estimators and 'asMSE'"
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-steps:
-[1] 1
-> 
-> ## 4.2 k-step estimation: radius unknown
-> ## take least favorable radius r = 0.579
-> ## cf. Table 8.1 in Kohl(2005)
-> ## choose k = 3
-> (est4 <- kStepEstimator(x, IC2, est0, steps = 3L))
-Evaluations of 3-step estimate:
--------------------------------
-An object of class “Estimate” 
-generated by call
-  kStepEstimator(x = x, IC = IC2, start = est0, steps = 3L)
-samplesize:   100
-estimate:
-      mean           sd     
-  -0.12006169    0.92637969 
- ( 0.10838143) ( 0.09628936)
-asymptotic (co)variance (multiplied with samplesize):
-         [,1]      [,2]
-[1,] 1.174653 0.0000000
-[2,] 0.000000 0.9271641
-Infos:
-     method          
-[1,] "kStepEstimator"
-[2,] "kStepEstimator"
-     message                                                        
-[1,] "3-step estimate for normal location and scale family"         
-[2,] "computation of IC, trafo, asvar and asbias via useLast = TRUE"
-asymptotic bias:
-       sd 
-0.9945548 
-(partial) influence curve:
-An object of class “ContIC” 
-### name:	 IC of contamination type 
-
-### L2-differentiable parametric family:	 normal location and scale family 
-### param:	An object of class "ParamWithScaleFamParameter"
-name:	location and scale
-mean:	-0.120061689892252
-sd:	0.926379689897674
-trafo:
-     mean sd
-mean    1  0
-sd      0  1
-
-### neighborhood radius:	 0.579 
-
-### clip:	      sd 
-1.717711 
-### cent:	[1]  0.0000000 -0.4389247
-### stand:
-         [,1]     [,2]
-[1,] 1.487853 0.000000
-[2,] 0.000000 1.192566
-
-### Infos:
-  method     message                                            
-  "rlOptIC"  "optimally robust IC for AL estimators and 'asMSE'"
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-  "modifyIC" "The IC has been modified"                         
-  "modifyIC" "The entries in 'Infos' may be wrong"              
-steps:
-[1] 3
-> 
-> 
-> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
+> cat("rlsOptIC.AL", get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
 > cleanEx()
 > nameEx("rlsOptIC.An1")
 > ### * rlsOptIC.An1
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: rlsOptIC.An1
 > ### Title: Computation of the optimally robust IC for An1 estimators
 > ### Aliases: rlsOptIC.An1
@@ -798,17 +582,24 @@
      method         message                                             
 [1,] "rlsOptIC.An1" "optimally robust IC for An1 estimators and 'asMSE'"
 [2,] "rlsOptIC.An1" "where a = 1.577"                                   
-> plot(IC1)
-> infoPlot(IC1)
+> ## don't run to reduce check time on CRAN
+> ## Not run: 
+> ##D plot(IC1)
+> ##D infoPlot(IC1)
+> ## End(Not run)
 > 
 > 
 > 
+> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
+> cat("rlsOptIC.An1", get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
 > cleanEx()
 > nameEx("rlsOptIC.An2")
 > ### * rlsOptIC.An2
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: rlsOptIC.An2
 > ### Title: Computation of the optimally robust IC for An2 estimators
 > ### Aliases: rlsOptIC.An2
@@ -840,16 +631,22 @@
 [1,] "rlsOptIC.An2" "optimally robust IC for An2 estimators and 'asMSE'"
 [2,] "rlsOptIC.An2" "where a = 1.813 and k = 2.267"                     
 > plot(IC1)
+NULL
+NULL
 > infoPlot(IC1)
 > 
 > 
 > 
+> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
+> cat("rlsOptIC.An2", get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
 > cleanEx()
 > nameEx("rlsOptIC.AnMad")
 > ### * rlsOptIC.AnMad
 > 
 > flush(stderr()); flush(stdout())
 > 
+> assign(".ptime", proc.time(), pos = "CheckExEnv")
 > ### Name: rlsOptIC.AnMad
 > ### Title: Computation of the optimally robust IC for AnMad estimators
 > ### Aliases: rlsOptIC.AnMad
@@ -881,16 +678,22 @@
 [1,] "rlsOptIC.AnMad" "optimally robust IC for AnMad estimators and 'asMSE'"
 [2,] "rlsOptIC.AnMad" "where a = 1.814"                                     
 > plot(IC1)
+NULL
+NULL
 > infoPlot(IC1)
 > 
 > 
 > 
+> 
+> assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/robast -r 577


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