[Robast-commits] r1329 - in branches/robast-1.3/pkg/RobLox: . inst tests/Examples

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Sun Jan 12 03:04:15 CET 2025


Author: ruckdeschel
Date: 2025-01-12 03:04:14 +0100 (Sun, 12 Jan 2025)
New Revision: 1329

Modified:
   branches/robast-1.3/pkg/RobLox/DESCRIPTION
   branches/robast-1.3/pkg/RobLox/inst/CITATION
   branches/robast-1.3/pkg/RobLox/inst/NEWS
   branches/robast-1.3/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save
Log:
[RobLox] ported changes from v 1.2.3 to branch 1.3

Modified: branches/robast-1.3/pkg/RobLox/DESCRIPTION
===================================================================
--- branches/robast-1.3/pkg/RobLox/DESCRIPTION	2025-01-12 02:02:56 UTC (rev 1328)
+++ branches/robast-1.3/pkg/RobLox/DESCRIPTION	2025-01-12 02:04:14 UTC (rev 1329)
@@ -1,22 +1,20 @@
 Package: RobLox
 Version: 1.3.0
-Date: 2019-03-13
+Date: 2025-01-12
 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 
-			(see Chapter 8 in Kohl (2005) <https://epub.uni-bayreuth.de/839/2/DissMKohl.pdf>).
+            estimators in case of normal location and/or scale (see Chapter 8 in Kohl (2005)
+            <https://epub.uni-bayreuth.de/839/2/DissMKohl.pdf>).
 Depends: R(>= 3.4), stats, distrMod(>= 2.8.0), RobAStBase(>= 1.2.0)
 Imports: methods, lattice, RColorBrewer, Biobase, RandVar(>= 1.2.0), distr(>= 2.8.0)
 Suggests: MASS
 Enhances: ROptEst
-Authors at R: c(person("Matthias", "Kohl", role=c("cre", "cph", "aut"),
-            email="Matthias.Kohl at stamats.de", comment = c(ORCID =
-            "0000-0001-9514-8910")), person("Peter", "Ruckdeschel", 
-			role=c("aut", "cph"), comment = c(ORCID = "0000-0001-7815-4809")))
+Authors at R: c(person("Matthias", "Kohl", role=c("cre", "cph"),
+            email="Matthias.Kohl at stamats.de"), person("Peter", "Ruckdeschel", role=c("aut",
+            "cph")))
 ByteCompile: yes
 License: LGPL-3
-Encoding: UTF-8
-URL: https://r-forge.r-project.org/projects/robast/
+URL: http://robast.r-forge.r-project.org/
 LastChangedDate: {$LastChangedDate$}
 LastChangedRevision: {$LastChangedRevision$}
-VCS/SVNRevision: 1205
+VCS/SVNRevision: 1327

Modified: branches/robast-1.3/pkg/RobLox/inst/CITATION
===================================================================
--- branches/robast-1.3/pkg/RobLox/inst/CITATION	2025-01-12 02:02:56 UTC (rev 1328)
+++ branches/robast-1.3/pkg/RobLox/inst/CITATION	2025-01-12 02:04:14 UTC (rev 1329)
@@ -5,8 +5,8 @@
 bibentry(
    bibtype = "Manual",
    mheader = "To cite package RobLox in publications use:",
-               title = "RobLox: Optimally robust influence curves and estimators for location and scale",
-         author = as.person("M. Kohl"),
+         title = "RobLox: Optimally robust influence curves and estimators for location and scale",
+         author = c(person("Matthias", "Kohl", comment = c(ORCID = "0000-0001-9514-8910"))),
          language = "English",
          year = year,
          note = note,

Modified: branches/robast-1.3/pkg/RobLox/inst/NEWS
===================================================================
--- branches/robast-1.3/pkg/RobLox/inst/NEWS	2025-01-12 02:02:56 UTC (rev 1328)
+++ branches/robast-1.3/pkg/RobLox/inst/NEWS	2025-01-12 02:04:14 UTC (rev 1329)
@@ -11,7 +11,12 @@
 version 1.3
 #######################################
 
-under the hood
+#######################################
+version 1.2.3
+#######################################
+
+under the hood:
++ adapted reference output for new startupmsg
 + fixed some broken URLs and changed URLs from http to https where possible
 + changed encoding to UTF-8 and updated URL for r-forge project homepage
 

Modified: branches/robast-1.3/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save
===================================================================
--- branches/robast-1.3/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save	2025-01-12 02:02:56 UTC (rev 1328)
+++ branches/robast-1.3/pkg/RobLox/tests/Examples/RobLox-Ex.Rout.save	2025-01-12 02:04:14 UTC (rev 1329)
@@ -1,1972 +1,1811 @@
-
-R Under development (unstable) (2013-02-06 r61845) -- "Unsuffered Consequences"
-Copyright (C) 2013 The R Foundation for Statistical Computing
-ISBN 3-900051-07-0
-Platform: x86_64-unknown-linux-gnu (64-bit)
-
-R is free software and comes with ABSOLUTELY NO WARRANTY.
-You are welcome to redistribute it under certain conditions.
-Type 'license()' or 'licence()' for distribution details.
-
-  Natural language support but running in an English locale
-
-R is a collaborative project with many contributors.
-Type 'contributors()' for more information and
-'citation()' on how to cite R or R packages in publications.
-
-Type 'demo()' for some demos, 'help()' for on-line help, or
-'help.start()' for an HTML browser interface to help.
-Type 'q()' to quit R.
-
-> pkgname <- "RobLox"
-> source(file.path(R.home("share"), "R", "examples-header.R"))
-> options(warn = 1)
-> library('RobLox')
-Loading required package: lattice
-Loading required package: RColorBrewer
-Loading required package: Biobase
-Loading required package: BiocGenerics
-Loading required package: parallel
-
-Attaching package: ‘BiocGenerics’
-
-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 objects are masked from ‘package:base’:
-
-    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
-
-    Vignettes contain introductory material; view with
-    'browseVignettes()'. To cite Bioconductor, see
-    'citation("Biobase")', and for packages 'citation("pkgname")'.
-
-Loading required package: distr
-Loading required package: startupmsg
-:startupmsg>  Utilities for start-up messages (version 0.8)
-:startupmsg> 
-:startupmsg>  For more information see ?"startupmsg",
-:startupmsg>  NEWS("startupmsg")
-
-Loading required package: sfsmisc
-Loading required package: SweaveListingUtils
-: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().
-:SweaveListingUtils> 
-:SweaveListingUtils>  Note that global options are
-:SweaveListingUtils>  controlled by
-:SweaveListingUtils>  SweaveListingoptions() ---c.f.
-:SweaveListingUtils>  ?"SweaveListingoptions".
-:SweaveListingUtils> 
-:SweaveListingUtils>  For more information see
-:SweaveListingUtils>  ?"SweaveListingUtils",
-:SweaveListingUtils>  NEWS("SweaveListingUtils")
-:SweaveListingUtils>  There is a vignette to this
-:SweaveListingUtils>  package; try
-:SweaveListingUtils>  vignette("ExampleSweaveListingUtils").
-
-
-Attaching package: ‘SweaveListingUtils’
-
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-
-    library, require
-
-:distr>  Object oriented implementation of distributions (version
-:distr>  2.4)
-:distr> 
-:distr>  Attention: Arithmetics on distribution objects are
-:distr>  understood as operations on corresponding random variables
-:distr>  (r.v.s); see distrARITH().
-:distr> 
-:distr>  Some functions from package 'stats' are intentionally masked
-:distr>  ---see distrMASK().
-:distr> 
-:distr>  Note that global options are controlled by distroptions()
-:distr>  ---c.f. ?"distroptions".
-:distr> 
-: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
-:distr>  well as to several extension packages; try
-:distr>  vignette("distr").
-
-
-Attaching package: ‘distr’
-
-The following object is masked from ‘package:stats’:
-
-    df, qqplot, sd
-
-Loading required package: distrMod
-Loading required package: distrEx
-:distrEx>  Extensions of package distr (version 2.4)
-:distrEx> 
-:distrEx>  Note: Packages "e1071", "moments", "fBasics" should be
-:distrEx>  attached /before/ package "distrEx". See
-:distrEx>  distrExMASK().Note: Extreme value distribution
-:distrEx>  functionality has been moved to
-:distrEx> 
-:distrEx>        package "RobExtremes". See distrExMOVED().
-:distrEx> 
-:distrEx>  For more information see ?"distrEx", NEWS("distrEx"), as
-:distrEx>  well as
-:distrEx>    http://distr.r-forge.r-project.org/
-:distrEx>  Package "distrDoc" provides a vignette to this package
-:distrEx>  as well as to several related packages; try
-:distrEx>  vignette("distr").
-
-
-Attaching package: ‘distrEx’
-
-The following object is masked from ‘package:stats’:
-
-    IQR, mad, median, var
-
-Loading required package: RandVar
-:RandVar>  Implementation of random variables (version 0.9)
-:RandVar> 
-:RandVar>  For more information see ?"RandVar", NEWS("RandVar"), as
-:RandVar>  well as
-:RandVar>    http://robast.r-forge.r-project.org/
-:RandVar>  This package also includes a vignette; try
-:RandVar>  vignette("RandVar").
-
-Loading required package: MASS
-Loading required package: stats4
-:distrMod>  Object oriented implementation of probability models
-:distrMod>  (version 2.4)
-:distrMod> 
-:distrMod>  Some functions from pkg's 'base' and 'stats' are
-:distrMod>  intentionally masked ---see distrModMASK().
-:distrMod> 
-:distrMod>  Note that global options are controlled by
-:distrMod>  distrModoptions() ---c.f. ?"distrModoptions".
-:distrMod> 
-:distrMod>  For more information see ?"distrMod",
-:distrMod>  NEWS("distrMod"), as well as
-:distrMod>    http://distr.r-forge.r-project.org/
-:distrMod>  There is a vignette to this package; try
-:distrMod>  vignette("distrMod").
-:distrMod>  Package "distrDoc" provides a vignette to the other
-:distrMod>  distrXXX packages,
-:distrMod>  as well as to several related packages; try
-:distrMod>  vignette("distr").
-
-
-Attaching package: ‘distrMod’
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-    confint
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-    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'
-:RobAStBase>  are intentionally masked ---see RobAStBaseMASK().
-:RobAStBase> 
-:RobAStBase>  Note that global options are controlled by
-:RobAStBase>  RobAStBaseoptions() ---c.f. ?"RobAStBaseoptions".
-:RobAStBase> 
-:RobAStBase>  For more information see ?"RobAStBase",
-:RobAStBase>  NEWS("RobAStBase"), as well as
-:RobAStBase>    http://robast.r-forge.r-project.org/
-
-
-Attaching package: ‘RobAStBase’
-
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-    clip
-
-> 
-> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
-> base::assign(".ExTimings", "RobLox-Ex.timings", pos = 'CheckExEnv')
-> base::cat("name\tuser\tsystem\telapsed\n", file=base::get(".ExTimings", pos = 'CheckExEnv'))
-> base::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())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: RobLox-package
-> ### Title: Optimally robust influence curves and estimators for location
-> ###   and scale
-> ### Aliases: RobLox-package RobLox
-> ### Keywords: package
-> 
-> ### ** Examples
-> 
-> library(RobLox)
-> ind <- rbinom(100, size=1, prob=0.05) 
-> x <- rnorm(100, mean=ind*3, sd=(1-ind) + ind*9)
-> roblox(x)
-Evaluations of Optimally robust estimate:
------------------------------------------
-An object of class “Estimate” 
-generated by call
-  roblox(x = x)
-samplesize:   100
-estimate:
-      mean           sd     
-  -0.14805155    0.88449633 
- ( 0.11247138) ( 0.08320902)
-asymptotic (co)variance (multiplied with samplesize):
-         [,1]     [,2]
-[1,] 1.264981 0.000000
-[2,] 0.000000 0.692374
-Infos:
-     method  
-[1,] "roblox"
-[2,] "roblox"
-[3,] "roblox"
-     message                                                                              
-[1,] "finite-sample corrected radius-minimax estimate for contamination interval [0, 0.5]"
-[2,] "least favorable (uncorrected) contamination: 0.057"                                 
-[3,] "maximum asymptotic MSE-inefficiency: 4.126"                                         
-asymptotic bias:
-[1] 1.885026
-steps:
-[1] 1
-> 
-> res <- roblox(x, eps.lower = 0.01, eps.upper = 0.1, returnIC = TRUE)
-> estimate(res)
-      mean         sd 
--0.1111504  0.8928424 
-> confint(res)
-A[n] asymptotic (LAN-based) confidence interval:
-          2.5 %     97.5 %
-mean -0.3066310 0.08433017
-sd    0.7472971 1.03838771
-Type of estimator: Optimally robust estimate
-samplesize:   100
-Call by which estimate was produced:
-roblox(x = x, eps.lower = 0.01, eps.upper = 0.1, returnIC = TRUE)
-> confint(res, method = symmetricBias())
-A[n] asymptotic (LAN-based), uniform (bias-aware)
- confidence interval:
-for symmetric Bias
-          2.5 %    97.5 %
-mean -0.3979957 0.1756949
-sd    0.6792714 1.1064134
-Type of estimator: Optimally robust estimate
-samplesize:   100
-Call by which estimate was produced:
-roblox(x = x, eps.lower = 0.01, eps.upper = 0.1, returnIC = TRUE)
-> pIC(res)
-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:	-0.111150435088066
-sd:	0.892842402157418
-trafo:
-     mean sd
-mean    1  0
-sd      0  1
-
-### neighborhood radius:	 0.5455335 
-
-### clip:	[1] 1.679196
-### cent:	[1]  0.000000 -0.382342
-### stand:
-         [,1]     [,2]
-[1,] 1.330601 0.000000
-[2,] 0.000000 1.054707
-
-### Infos:
-     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"                                            
-> 
-> ## 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)
-> rowRoblox(X)
-Evaluations of Optimally robust estimate:
------------------------------------------
-An object of class “Estimate” 
-generated by call
-  rowRoblox(x = X)
-samplesize:   100
-estimate:
-            mean        sd
-[1,] -0.09216816 1.1317057
-[2,]  0.10169428 0.9520219
-Infos:
-     method   message                                                       
-[1,] "roblox" "radius-minimax estimates for contamination interval [0, 0.5]"
-[2,] "roblox" "least favorable contamination: 0.13"                         
-[3,] "roblox" "maximum MSE-inefficiency: 1.668"                             
-asymptotic bias:
-NULL
-steps:
-[1] 1
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("0RobLox-package", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("finiteSampleCorrection")
-> ### * finiteSampleCorrection
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: finiteSampleCorrection
-> ### Title: Function to compute finite-sample corrected radii
-> ### Aliases: finiteSampleCorrection
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> finiteSampleCorrection(n = 3, r = 0.001, model = "locsc")
-[1] 0.0296
-> finiteSampleCorrection(n = 10, r = 0.02, model = "loc")
-[1] 0.0779657
-> finiteSampleCorrection(n = 250, r = 0.15, model = "sc")
-[1] 0.7348683
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("finiteSampleCorrection", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlOptIC")
-> ### * rlOptIC
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlOptIC
-> ### Title: Computation of the optimally robust IC for AL estimators
-> ### Aliases: rlOptIC
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlOptIC(r = 0.1)
-> distrExOptions("ErelativeTolerance" = 1e-12)
-> checkIC(IC1)
-precision of centering:	 0 
-precision of Fisher consistency:
-              mean
-mean -7.580384e-06
-maximum deviation 
-     7.580384e-06 
-> distrExOptions("ErelativeTolerance" = .Machine$double.eps^0.25) # default
-> Risks(IC1)
-$asMSE
-[1] 1.054162
-
-$asBias
-[1] 2.053826
-
-$asCov
-[1] 1.01198
-
-> cent(IC1)
-[1] 0
-> clip(IC1)
-[1] 2.053826
-> stand(IC1)
-         [,1]
-[1,] 1.054162
-> plot(IC1)
-NULL
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlOptIC", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.AL")
-> ### * rlsOptIC.AL
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.AL
-> ### Title: Computation of the optimally robust IC for AL estimators
-> ### Aliases: rlsOptIC.AL
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.AL(r = 0.1, check = TRUE)
-Fisher consistency of eta.loc:	 -1.743783e-10 
-centering of eta.sc:	 -3.904033e-10 
-Fisher consistency of eta.sc:	 2.926179e-09 
-MSE equation:	 1.207368e-14 
-> distrExOptions("ErelativeTolerance" = 1e-12)
-> checkIC(IC1)
-precision of centering:	 0 -6.039278e-07 
-precision of Fisher consistency:
-             mean            sd
-mean -1.10248e-06  0.000000e+00
-sd    0.00000e+00 -1.685676e-05
-maximum deviation 
-     1.685676e-05 
-> distrExOptions("ErelativeTolerance" = .Machine$double.eps^0.25) # default
-> Risks(IC1)
-$asMSE
-[1] 1.647765
-
-$asBias
-[1] 3.182504
-
-$trAsCov
-[1] 1.546482
-
-$asCov
-         [,1]      [,2]
-[1,] 1.017104 0.0000000
-[2,] 0.000000 0.5293779
-
-> cent(IC1)
-[1]  0.00000000 -0.02574219
-> clip(IC1)
-[1] 3.182504
-> stand(IC1)
-        [,1]      [,2]
-[1,] 1.05189 0.0000000
-[2,] 0.00000 0.5958748
-> 
-> ## 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)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.AL", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.An1")
-> ### * rlsOptIC.An1
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.An1
-> ### Title: Computation of the optimally robust IC for An1 estimators
-> ### Aliases: rlsOptIC.An1
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.An1(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 1.410025e-07 
-precision of Fisher consistency:
-             mean           sd
-mean 2.530605e-08 0.000000e+00
-sd   0.000000e+00 3.875467e-06
-maximum deviation 
-     3.875467e-06 
-> Risks(IC1)
-$asMSE
-[1] 1.673449
-
-$asBias
-[1] 3.341956
-
-$asCov
-[1] 1.561762
-
-> Infos(IC1)
-     method         message                                             
-[1,] "rlsOptIC.An1" "optimally robust IC for An1 estimators and 'asMSE'"
-[2,] "rlsOptIC.An1" "where a = 1.577"                                   
-> ## don't run to reduce check time on CRAN
-> ## Not run: 
-> ##D plot(IC1)
-> ##D infoPlot(IC1)
-> ## End(Not run)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.An1", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.An2")
-> ### * rlsOptIC.An2
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.An2
-> ### Title: Computation of the optimally robust IC for An2 estimators
-> ### Aliases: rlsOptIC.An2
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.An2(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -0.0001066371 
-precision of Fisher consistency:
-              mean            sd
-mean -4.006394e-07  0.000000e+00
-sd    0.000000e+00 -1.496408e-05
-maximum deviation 
-     0.0001066371 
-> Risks(IC1)
-$asMSE
-[1] 1.656837
-
-$asBias
-[1] 3.268231
-
-$asCov
-[1] 1.550024
-
-> Infos(IC1)
-     method         message                                             
-[1,] "rlsOptIC.An2" "optimally robust IC for An2 estimators and 'asMSE'"
-[2,] "rlsOptIC.An2" "where a = 1.813 and k = 2.267"                     
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.An2", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.AnMad")
-> ### * rlsOptIC.AnMad
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.AnMad
-> ### Title: Computation of the optimally robust IC for AnMad estimators
-> ### Aliases: rlsOptIC.AnMad
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.AnMad(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -6.569591e-07 
-precision of Fisher consistency:
-              mean            sd
-mean -4.044557e-07  0.000000e+00
-sd    0.000000e+00 -6.821323e-05
-maximum deviation 
-     6.821323e-05 
-> Risks(IC1)
-$asMSE
-[1] 2.434119
-
-$asBias
-[1] 2.412581
-
-$asCov
-[1] 2.375914
-
-> Infos(IC1)
-     method           message                                               
-[1,] "rlsOptIC.AnMad" "optimally robust IC for AnMad estimators and 'asMSE'"
-[2,] "rlsOptIC.AnMad" "where a = 1.814"                                     
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.AnMad", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.BM")
-> ### * rlsOptIC.BM
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.BM
-> ### Title: Computation of the optimally robust IC for BM estimators
-> ### Aliases: rlsOptIC.BM
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.BM(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -1.246469e-06 
-precision of Fisher consistency:
-              mean            sd
-mean -2.355426e-06  0.000000e+00
-sd    0.000000e+00 -1.737383e-05
-maximum deviation 
-     1.737383e-05 
-> Risks(IC1)
-$asMSE
-[1] 1.659506
-
-$asBias
-[1] 3.339524
-
-$asCov
-[1] 1.547982
-
-> Infos(IC1)
-     method       
-[1,] "rlsOptIC.BM"
-[2,] "rlsOptIC.BM"
-     message                                                                  
-[1,] "optimally robust IC for BM estimators and 'asMSE'"                      
-[2,] " where b.loc = 2.121 , b.sc.0 = 4.461 , alpha = 1.053 and gamma = 0.578"
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.BM", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.Ha3")
-> ### * rlsOptIC.Ha3
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.Ha3
-> ### Title: Computation of the optimally robust IC for Ha3 estimators
-> ### Aliases: rlsOptIC.Ha3
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.Ha3(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -2.659214e-07 
-precision of Fisher consistency:
-              mean            sd
-mean -8.538336e-07  0.000000e+00
-sd    0.000000e+00 -9.691769e-06
-maximum deviation 
-     9.691769e-06 
-> Risks(IC1)
-$asMSE
-[1] 1.649969
-
-$asBias
-[1] 3.215669
-
-$asCov
-[1] 1.546563
-
-> Infos(IC1)
-     method         message                                             
-[1,] "rlsOptIC.Ha3" "optimally robust IC for Ha3 estimators and 'asMSE'"
-[2,] "rlsOptIC.Ha3" "where a = 2.132 , b = 2.17 and c = 7.059"          
-> ## don't run to reduce check time on CRAN
-> ## Not run: 
-> ##D plot(IC1)
-> ##D infoPlot(IC1)
-> ## End(Not run)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.Ha3", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.Ha4")
-> ### * rlsOptIC.Ha4
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.Ha4
-> ### Title: Computation of the optimally robust IC for Ha4 estimators
-> ### Aliases: rlsOptIC.Ha4
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.Ha4(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -0.0001069318 
-precision of Fisher consistency:
-              mean            sd
-mean -2.265319e-06  0.000000e+00
-sd    0.000000e+00 -1.498731e-05
-maximum deviation 
-     0.0001069318 
-> Risks(IC1)
-$asMSE
-[1] 1.650944
-
-$asBias
-[1] 3.230698
-
-$asCov
-[1] 1.54657
-
-> Infos(IC1)
-     method         message                                               
-[1,] "rlsOptIC.Ha4" "optimally robust IC for Ha4 estimators and 'asMSE'"  
-[2,] "rlsOptIC.Ha4" "where a = 1.947 , b = 5.244 , c = 6.34 and k = 2.267"
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.Ha4", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.HaMad")
-> ### * rlsOptIC.HaMad
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.HaMad
-> ### Title: Computation of the optimally robust IC for HuMad estimators
-> ### Aliases: rlsOptIC.HaMad
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.HaMad(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -6.569591e-07 
-precision of Fisher consistency:
-              mean            sd
-mean -2.041724e-06  0.000000e+00
-sd    0.000000e+00 -6.821323e-05
-maximum deviation 
-     6.821323e-05 
-> Risks(IC1)
-$asMSE
-[1] 2.428232
-
-$asBias
-[1] 2.358787
-
-$asCov
-[1] 2.372593
-
-> Infos(IC1)
-     method           message                                               
-[1,] "rlsOptIC.HaMad" "optimally robust IC for HaMad estimators and 'asMSE'"
-[2,] "rlsOptIC.HaMad" "where a = 1.944 , b = 4.368 , c = 10.51"             
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.HaMad", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.Hu1")
-> ### * rlsOptIC.Hu1
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.Hu1
-> ### Title: Computation of the optimally robust IC for Hu1 estimators
-> ### Aliases: rlsOptIC.Hu1
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.Hu1(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -2.085425e-06 
-precision of Fisher consistency:
-              mean            sd
-mean -3.746843e-06  0.000000e+00
-sd    0.000000e+00 -1.350353e-05
-maximum deviation 
-     1.350353e-05 
-> Risks(IC1)
-$asMSE
-[1] 1.654518
-
-$asBias
-[1] 3.281352
-
-$asCov
-[1] 1.546845
-
-> Infos(IC1)
-     method         message                                             
-[1,] "rlsOptIC.Hu1" "optimally robust IC for Hu1 estimators and 'asMSE'"
-[2,] "rlsOptIC.Hu1" "where k = 2.197"                                   
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.Hu1", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.Hu2")
-> ### * rlsOptIC.Hu2
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.Hu2
-> ### Title: Computation of the optimally robust IC for Hu2 estimators
-> ### Aliases: rlsOptIC.Hu2
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.Hu2(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -6.187336e-07 
-precision of Fisher consistency:
-              mean            sd
-mean -2.563384e-06  0.000000e+00
-sd    0.000000e+00 -1.321969e-05
-maximum deviation 
-     1.321969e-05 
-> Risks(IC1)
-$asMSE
-[1] 1.650944
-
-$asBias
-[1] 3.227897
-
-$asCov
-[1] 1.546751
-
-> Infos(IC1)
-     method         message                                             
-[1,] "rlsOptIC.Hu2" "optimally robust IC for Hu2 estimators and 'asMSE'"
-[2,] "rlsOptIC.Hu2" "where k = 1.945 and c = 2.266"                     
-> plot(IC1)
-NULL
-NULL
-> infoPlot(IC1)
-> 
-> 
-> 
-> 
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("rlsOptIC.Hu2", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
-> cleanEx()
-> nameEx("rlsOptIC.Hu2a")
-> ### * rlsOptIC.Hu2a
-> 
-> flush(stderr()); flush(stdout())
-> 
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: rlsOptIC.Hu2a
-> ### Title: Computation of the optimally robust IC for Hu2a estimators
-> ### Aliases: rlsOptIC.Hu2a
-> ### Keywords: robust
-> 
-> ### ** Examples
-> 
-> IC1 <- rlsOptIC.Hu2a(r = 0.1)
-> checkIC(IC1)
-precision of centering:	 0 -1.52497e-06 
-precision of Fisher consistency:
-             mean            sd
-mean -3.15714e-06  0.000000e+00
-sd    0.00000e+00 -1.321476e-05
-maximum deviation 
-     1.321476e-05 
-> Risks(IC1)
-$asMSE
-[1] 1.654518
-
-$asBias
-[1] 3.283358
-
-$asCov
-[1] 1.546714
-
-> Infos(IC1)
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/robast -r 1329


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