[Robast-commits] r886 - pkg/RobAStBase
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Sep 1 16:13:04 CEST 2016
Author: ruckdeschel
Date: 2016-09-01 16:13:04 +0200 (Thu, 01 Sep 2016)
New Revision: 886
Removed:
pkg/RobAStBase/RobAStBase-Ex.R
Modified:
pkg/RobAStBase/
Log:
RobAStBase-Ex.R unversioned
Property changes on: pkg/RobAStBase
___________________________________________________________________
Added: svn:ignore
+ RobAStBase-Ex.R
Deleted: pkg/RobAStBase/RobAStBase-Ex.R
===================================================================
--- pkg/RobAStBase/RobAStBase-Ex.R 2016-09-01 14:11:58 UTC (rev 885)
+++ pkg/RobAStBase/RobAStBase-Ex.R 2016-09-01 14:13:04 UTC (rev 886)
@@ -1,1102 +0,0 @@
-pkgname <- "RobAStBase"
-source(file.path(R.home("share"), "R", "examples-header.R"))
-options(warn = 1)
-options(pager = "console")
-library('RobAStBase')
-
-assign(".oldSearch", search(), pos = 'CheckExEnv')
-cleanEx()
-nameEx("0RobAStBase-package")
-### * 0RobAStBase-package
-
-flush(stderr()); flush(stdout())
-
-### Name: RobAStBase-package
-### Title: Robust Asymptotic Statistics
-### Aliases: RobAStBase-package RobAStBase
-### Keywords: package
-
-### ** Examples
-
-library(RobAStBase)
-
-## some L2 differentiable parametric family from package distrMod, e.g.
-B <- BinomFamily(size = 25, prob = 0.25)
-
-## classical optimal IC
-IC0 <- optIC(model = B, risk = asCov())
-plot(IC0) # plot IC
-checkIC(IC0, B)
-
-
-
-cleanEx()
-nameEx("ALEstimate-class")
-### * ALEstimate-class
-
-flush(stderr()); flush(stdout())
-
-### Name: ALEstimate-class
-### Title: ALEstimate-class.
-### Aliases: ALEstimate-class pIC pIC,ALEstimate-method asbias
-### asbias,ALEstimate-method show,ALEstimate-method
-### confint,ALEstimate,missing-method
-### confint,ALEstimate,symmetricBias-method
-### confint,ALEstimate,onesidedBias-method
-### confint,ALEstimate,asymmetricBias-method
-### Keywords: classes
-
-### ** Examples
-
-## prototype
-new("ALEstimate")
-
-
-
-cleanEx()
-nameEx("BdStWeight-class")
-### * BdStWeight-class
-
-flush(stderr()); flush(stdout())
-
-### Name: BdStWeight-class
-### Title: Robust Weight classes for bounded, standardized weights
-### Aliases: BdStWeight-class stand,BdStWeight-method
-### stand<-,BdStWeight-method
-### Keywords: classes
-
-### ** Examples
-
-## prototype
-new("BdStWeight")
-
-
-
-cleanEx()
-nameEx("BoundedWeight-class")
-### * BoundedWeight-class
-
-flush(stderr()); flush(stdout())
-
-### Name: BoundedWeight-class
-### Title: Robust Weight classes for bounded weights
-### Aliases: BoundedWeight-class clip,BoundedWeight-method
-### clip<-,BoundedWeight-method
-### Keywords: classes
-
-### ** Examples
-
-## prototype
-new("BoundedWeight")
-
-
-
-cleanEx()
-nameEx("ContIC-class")
-### * ContIC-class
-
-flush(stderr()); flush(stdout())
-
-### Name: ContIC-class
-### Title: Influence curve of contamination type
-### Aliases: ContIC-class CallL2Fam<-,ContIC-method cent cent,ContIC-method
-### cent<- cent<-,ContIC-method clip,ContIC-method clip<-
-### clip<-,ContIC-method lowerCase<- lowerCase<-,ContIC-method stand<-
-### stand<-,ContIC-method neighbor,ContIC-method
-### generateIC,ContNeighborhood,L2ParamFamily-method show,ContIC-method
-### Keywords: classes
-
-### ** Examples
-
-IC1 <- new("ContIC")
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("ContIC")
-### * ContIC
-
-flush(stderr()); flush(stdout())
-
-### Name: ContIC
-### Title: Generating function for ContIC-class
-### Aliases: ContIC
-### Keywords: robust
-
-### ** Examples
-
-IC1 <- ContIC()
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("ContNeighborhood-class")
-### * ContNeighborhood-class
-
-flush(stderr()); flush(stdout())
-
-### Name: ContNeighborhood-class
-### Title: Contamination Neighborhood
-### Aliases: ContNeighborhood-class
-### Keywords: classes models
-
-### ** Examples
-
-new("ContNeighborhood")
-
-
-
-cleanEx()
-nameEx("ContNeighborhood")
-### * ContNeighborhood
-
-flush(stderr()); flush(stdout())
-
-### Name: ContNeighborhood
-### Title: Generating function for ContNeighborhood-class
-### Aliases: ContNeighborhood
-### Keywords: models
-
-### ** Examples
-
-ContNeighborhood()
-
-## The function is currently defined as
-function(radius = 0){
- new("ContNeighborhood", radius = radius)
-}
-
-
-
-cleanEx()
-nameEx("FixRobModel-class")
-### * FixRobModel-class
-
-flush(stderr()); flush(stdout())
-
-### Name: FixRobModel-class
-### Title: Robust model with fixed (unconditional) neighborhood
-### Aliases: FixRobModel-class neighbor<-,FixRobModel-method
-### show,FixRobModel-method
-### Keywords: classes models
-
-### ** Examples
-
-new("FixRobModel")
-
-
-
-cleanEx()
-nameEx("FixRobModel")
-### * FixRobModel
-
-flush(stderr()); flush(stdout())
-
-### Name: FixRobModel
-### Title: Generating function for FixRobModel-class
-### Aliases: FixRobModel
-### Keywords: models
-
-### ** Examples
-
-(M1 <- FixRobModel())
-
-## The function is currently defined as
-function(center = ParamFamily(), neighbor = ContNeighborhood()){
- new("FixRobModel", center = center, neighbor = neighbor)
-}
-
-
-
-cleanEx()
-nameEx("HampIC-class")
-### * HampIC-class
-
-flush(stderr()); flush(stdout())
-
-### Name: HampIC-class
-### Title: Influence curve of Hampel type
-### Aliases: HampIC-class lowerCase lowerCase,HampIC-method neighborRadius
-### neighborRadius,HampIC-method neighborRadius<-
-### neighborRadius<-,HampIC-method stand stand,HampIC-method
-### weight,HampIC-method biastype,HampIC-method normtype,HampIC-method
-### Keywords: classes
-
-### ** Examples
-
-IC1 <- new("HampIC")
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("HampelWeight-class")
-### * HampelWeight-class
-
-flush(stderr()); flush(stdout())
-
-### Name: HampelWeight-class
-### Title: Robust Weight classes for weights of Hampel type
-### Aliases: HampelWeight-class cent,HampelWeight-method
-### cent<-,HampelWeight-method
-### Keywords: classes
-
-### ** Examples
-
-## prototype
-new("HampelWeight")
-
-
-
-cleanEx()
-nameEx("IC-class")
-### * IC-class
-
-flush(stderr()); flush(stdout())
-
-### Name: IC-class
-### Title: Influence curve
-### Aliases: IC-class CallL2Fam CallL2Fam,IC-method CallL2Fam<-
-### CallL2Fam<-,IC-method modifyIC modifyIC,IC-method
-### checkIC,IC,missing-method checkIC,IC,L2ParamFamily-method
-### evalIC,IC,numeric-method evalIC,IC,matrix-method show,IC-method
-### Keywords: classes robust
-
-### ** Examples
-
-IC1 <- new("IC")
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("IC")
-### * IC
-
-flush(stderr()); flush(stdout())
-
-### Name: IC
-### Title: Generating function for IC-class
-### Aliases: IC
-### Keywords: robust
-
-### ** Examples
-
-IC1 <- IC()
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("InfRobModel-class")
-### * InfRobModel-class
-
-flush(stderr()); flush(stdout())
-
-### Name: InfRobModel-class
-### Title: Robust model with infinitesimal (unconditional) neighborhood
-### Aliases: InfRobModel-class neighbor<-,InfRobModel-method
-### show,InfRobModel-method
-### Keywords: classes models
-
-### ** Examples
-
-new("InfRobModel")
-
-
-
-cleanEx()
-nameEx("InfRobModel")
-### * InfRobModel
-
-flush(stderr()); flush(stdout())
-
-### Name: InfRobModel
-### Title: Generating function for InfRobModel-class
-### Aliases: InfRobModel
-### Keywords: models
-
-### ** Examples
-
-(M1 <- InfRobModel())
-
-## The function is currently defined as
-function(center = L2ParamFamily(), neighbor = ContNeighborhood()){
- new("InfRobModel", center = center, neighbor = neighbor)
-}
-
-
-
-cleanEx()
-nameEx("InfluenceCurve-class")
-### * InfluenceCurve-class
-
-flush(stderr()); flush(stdout())
-
-### Name: InfluenceCurve-class
-### Title: Influence curve
-### Aliases: InfluenceCurve-class addInfo<- addInfo<-,InfluenceCurve-method
-### addRisk<- addRisk<-,InfluenceCurve-method Curve
-### Curve,InfluenceCurve-method Domain,InfluenceCurve-method Infos
-### Infos,InfluenceCurve-method Infos<- Infos<-,InfluenceCurve-method
-### Map,InfluenceCurve-method name,InfluenceCurve-method
-### name<-,InfluenceCurve-method Range,InfluenceCurve-method Risks
-### Risks,InfluenceCurve-method Risks<- Risks<-,InfluenceCurve-method
-### show,InfluenceCurve-method
-### Keywords: classes robust
-
-### ** Examples
-
-new("InfluenceCurve")
-
-
-
-cleanEx()
-nameEx("InfluenceCurve")
-### * InfluenceCurve
-
-flush(stderr()); flush(stdout())
-
-### Name: InfluenceCurve
-### Title: Generating function for InfluenceCurve-class
-### Aliases: InfluenceCurve
-### Keywords: robust
-
-### ** Examples
-
-InfluenceCurve()
-
-## The function is currently defined as
-InfluenceCurve <- function(name, Curve = EuclRandVarList(EuclRandVariable(Domain = Reals())),
- Risks, Infos){
- if(missing(name))
- name <- "influence curve"
- if(missing(Risks))
- Risks <- list()
- if(missing(Infos))
- Infos <- matrix(c(character(0),character(0)), ncol=2,
- dimnames=list(character(0), c("method", "message")))
-
- return(new("InfluenceCurve", name = name, Curve = Curve,
- Risks = Risks, Infos = Infos))
-}
-
-
-
-cleanEx()
-nameEx("MEstimate-class")
-### * MEstimate-class
-
-flush(stderr()); flush(stdout())
-
-### Name: MEstimate-class
-### Title: MEstimate-class.
-### Aliases: MEstimate-class Mroot Mroot,MEstimate-method
-### show,MEstimate-method
-### Keywords: classes
-
-### ** Examples
-
-## prototype
-new("MEstimate")
-
-
-
-cleanEx()
-nameEx("RobAStBaseMASK")
-### * RobAStBaseMASK
-
-flush(stderr()); flush(stdout())
-
-### Name: RobAStBaseMASK
-### Title: Masking of/by other functions in package "RobAStBase"
-### Aliases: RobAStBaseMASK MASKING
-### Keywords: programming distribution documentation
-
-### ** Examples
-
-RobAStBaseMASK()
-
-
-
-cleanEx()
-nameEx("RobAStBaseOptions")
-### * RobAStBaseOptions
-
-flush(stderr()); flush(stdout())
-
-### Name: RobAStBaseOptions
-### Title: Function to change the global variables of the package
-### 'RobAStBase'
-### Aliases: RobAStBaseOptions getRobAStBaseOption kStepUseLast
-### Keywords: misc robust
-
-### ** Examples
-
-RobAStBaseOptions()
-RobAStBaseOptions("kStepUseLast")
-RobAStBaseOptions("kStepUseLast" = TRUE)
-# or
-RobAStBaseOptions(kStepUseLast = 1e-6)
-getRobAStBaseOption("kStepUseLast")
-
-
-
-cleanEx()
-nameEx("RobWeight-class")
-### * RobWeight-class
-
-flush(stderr()); flush(stdout())
-
-### Name: RobWeight-class
-### Title: Robust Weight classes
-### Aliases: RobWeight-class name,RobWeight-method name<-,RobWeight-method
-### weight weight,RobWeight-method weight<- weight<--methods
-### weight<-,RobWeight-method
-### Keywords: classes
-
-### ** Examples
-
-## prototype
-new("RobWeight")
-
-
-
-cleanEx()
-nameEx("TotalVarIC-class")
-### * TotalVarIC-class
-
-flush(stderr()); flush(stdout())
-
-### Name: TotalVarIC-class
-### Title: Influence curve of total variation type
-### Aliases: TotalVarIC-class CallL2Fam<-,TotalVarIC-method clipLo
-### clip,TotalVarIC-method clipLo,TotalVarIC-method clipLo<-
-### clipLo<-,TotalVarIC-method clipUp clipUp,TotalVarIC-method clipUp<-
-### clipUp<-,TotalVarIC-method lowerCase<-,TotalVarIC-method
-### neighbor,TotalVarIC-method show,TotalVarIC-method
-### stand<-,TotalVarIC-method
-### generateIC,TotalVarNeighborhood,L2ParamFamily-method
-### Keywords: classes robust
-
-### ** Examples
-
-IC1 <- new("TotalVarIC")
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("TotalVarIC")
-### * TotalVarIC
-
-flush(stderr()); flush(stdout())
-
-### Name: TotalVarIC
-### Title: Generating function for TotalVarIC-class
-### Aliases: TotalVarIC
-### Keywords: robust
-
-### ** Examples
-
-IC1 <- TotalVarIC()
-plot(IC1)
-
-
-
-cleanEx()
-nameEx("TotalVarNeighborhood-class")
-### * TotalVarNeighborhood-class
-
-flush(stderr()); flush(stdout())
-
-### Name: TotalVarNeighborhood-class
-### Title: Total variation neighborhood
-### Aliases: TotalVarNeighborhood-class
-### Keywords: classes models
-
-### ** Examples
-
-new("TotalVarNeighborhood")
-
-
-
-cleanEx()
-nameEx("TotalVarNeighborhood")
-### * TotalVarNeighborhood
-
-flush(stderr()); flush(stdout())
-
-### Name: TotalVarNeighborhood
-### Title: Generating function for TotalVarNeighborhood-class
-### Aliases: TotalVarNeighborhood
-### Keywords: models
-
-### ** Examples
-
-TotalVarNeighborhood()
-
-## The function is currently defined as
-function(radius = 0){
- new("TotalVarNeighborhood", radius = radius)
-}
-
-
-
-cleanEx()
-nameEx("checkIC")
-### * checkIC
-
-flush(stderr()); flush(stdout())
-
-### Name: checkIC
-### Title: Generic Function for Checking ICs
-### Aliases: checkIC
-### Keywords: robust
-
-### ** Examples
-
-IC1 <- new("IC")
-checkIC(IC1)
-
-
-
-cleanEx()
-nameEx("comparePlot")
-### * comparePlot
-
-flush(stderr()); flush(stdout())
-
-### Name: comparePlot-methods
-### Title: Compare - Plots
-### Aliases: comparePlot comparePlot-methods comparePlot,IC,IC-method
-### Keywords: robust
-
-### ** Examples
-
-if(require(ROptEst)){
-
-N0 <- NormLocationScaleFamily(mean=0, sd=1)
-N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 0.5))
-
-IC1 <- optIC(model = N0, risk = asCov())
-IC2 <- optIC(model = N0.Rob1, risk = asMSE())
-
-comparePlot(IC1,IC2)
-
-set.seed(12); data <- r(N0)(20)
-comparePlot(IC1, IC2, data=data, with.lab = TRUE,
- which.lbs = c(1:4,15:20),
- which.Order = 1:6,
- return.Order = TRUE)
-
-## don't run to reduce check time on CRAN
-## Not run:
-##D ## selection of subpanels for plotting
-##D par(mfrow=c(1,1))
-##D comparePlot(IC1, IC2 ,mfColRow = FALSE, to.draw.arg=c("mean"),
-##D panel.first= grid(),ylim=c(-4,4),xlim=c(-6,6))
-##D ## matrix-valued ylim
-##D comparePlot(IC1, IC2, panel.first= grid(),ylim=c(-4,4,0,4),xlim=c(-6,6))
-##D
-##D x <- c(data,-12,10)
-##D comparePlot(IC1, IC2, data=x, which.Order=10,
-##D panel.first= grid(), ylim=c(-4,4,0,4), xlim=c(-6,6))
-##D
-##D Y <- Chisq(df=1)* DiscreteDistribution(c(-1,1))
-##D comparePlot(IC1, IC2, data=x, which.Order=10,
-##D scaleX = TRUE, scaleX.fct=pnorm, scaleX.inv=qnorm,
-##D scaleY = TRUE, scaleY.fct=p(Y), scaleY.inv=q(Y),
-##D panel.first= grid(), ylim=c(-4,4,0,4), xlim=c(-6,6))
-##D comparePlot(IC1, IC2, data=x, which.Order=10,
-##D scaleX = TRUE, scaleX.fct=pnorm, scaleX.inv=qnorm,
-##D scaleY = TRUE, scaleY.fct=p(Y), scaleY.inv=q(Y),
-##D x.ticks = c(-Inf, -10, -1,0,1,10,Inf),
-##D y.ticks = c(-Inf, -5, -1,0,1,5,Inf),
-##D panel.first= grid(), ylim=c(-4,4,0,4), xlim=c(-6,6))
-##D
-##D ## with use of trafo-matrix:
-##D G <- GammaFamily(scale = 1, shape = 2)
-##D ## explicitely transforming to
-##D ## MASS parametrization:
-##D mtrafo <- function(x){
-##D nms0 <- names(c(main(param(G)),nuisance(param(G))))
-##D nms <- c("shape","rate")
-##D fval0 <- c(x[2], 1/x[1])
-##D names(fval0) <- nms
-##D mat0 <- matrix( c(0, -1/x[1]^2, 1, 0), nrow = 2, ncol = 2,
-##D dimnames = list(nms,nms0))
-##D list(fval = fval0, mat = mat0)}
-##D G2 <- G
-##D trafo(G2) <- mtrafo
-##D G2
-##D G2.Rob1 <- InfRobModel(center = G2, neighbor = ContNeighborhood(radius = 0.5))
-##D system.time(IC1 <- optIC(model = G2, risk = asCov()))
-##D system.time(IC2 <- optIC(model = G2.Rob1, risk = asMSE()))
-##D system.time(IC2.i <- optIC(model = G2.Rob1, risk = asMSE(normtype=InfoNorm())))
-##D system.time(IC2.s <- optIC(model = G2.Rob1, risk = asMSE(normtype=SelfNorm())))
-##D
-##D comparePlot(IC1,IC2, IC2.i, IC2.s)
-## End(Not run)
-
-}
-
-
-
-cleanEx()
-nameEx("cutoff-class")
-### * cutoff-class
-
-flush(stderr()); flush(stdout())
-
-### Name: cutoff-class
-### Title: Cutoff class for distance-distance plots
-### Aliases: cutoff-class cutoff.quantile<-,cutoff-method cutoff.quantile<-
-### cutoff.quantile,cutoff-method cutoff.quantile name,cutoff-method
-### fct,cutoff-method
-### Keywords: classes
-
-### ** Examples
-
-cutoff()
-
-
-
-cleanEx()
-nameEx("cutoff")
-### * cutoff
-
-flush(stderr()); flush(stdout())
-
-### Name: cutoff
-### Title: Generating function(s) for class 'cutoff'
-### Aliases: cutoff cutoff.sememp cutoff.chisq
-### Keywords: hplot
-
-### ** Examples
-
-cutoff()
-cutoff.sememp()
-cutoff.chisq()
-
-
-
-cleanEx()
-nameEx("ddPlot-methods")
-### * ddPlot-methods
-
-flush(stderr()); flush(stdout())
-
-### Name: ddPlot-methods
-### Title: Methods for Function ddPlot in Package 'RobAStBase'
-### Aliases: ddPlot ddPlot-methods ddPlot,matrix-method
-### ddPlot,numeric-method ddPlot,data.frame-method
-### Keywords: methods hplot
-
-### ** Examples
-
-MX <- matrix(rnorm(1500),nrow=6)
-QM <- matrix(rnorm(36),nrow=6); QM <- QM %*% t(QM)
-ddPlot(data=MX, dist.y=QFNorm(QuadF=PosSemDefSymmMatrix(QM)))
-
-
-
-cleanEx()
-nameEx("getRiskFctBV-methods")
-### * getRiskFctBV-methods
-
-flush(stderr()); flush(stdout())
-
-### Name: getRiskFctBV-methods
-### Title: Methods for Function getRiskFctBV in Package 'RobAStBase'
-### Aliases: getRiskFctBV getRiskFctBV-methods
-### getRiskFctBV,asGRisk,ANY-method getRiskFctBV,asMSE,ANY-method
-### getRiskFctBV,asSemivar,onesidedBias-method
-### getRiskFctBV,asSemivar,asymmetricBias-method
-### Keywords: classes
-
-### ** Examples
-
-myrisk <- asMSE()
-getRiskFctBV(myrisk)
-
-
-
-cleanEx()
-nameEx("infoPlot")
-### * infoPlot
-
-flush(stderr()); flush(stdout())
-
-### Name: infoPlot
-### Title: Plot absolute and relative information
-### Aliases: infoPlot infoPlot-methods infoPlot,IC-method
-### Keywords: robust
-
-### ** Examples
-
-N <- NormLocationScaleFamily(mean=0, sd=1)
-IC1 <- optIC(model = N, risk = asCov())
-infoPlot(IC1)
-
-## don't run to reduce check time on CRAN
-## Not run:
-##D ## selection of subpanels for plotting
-##D par(mfrow=c(1,2))
-##D infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","sd"))
-##D infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","sd"), log="y")
-##D
-##D infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","mean"),
-##D panel.first= grid(), ylim = c(0,4), xlim = c(-6,6))
-##D infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","mean"),
-##D panel.first= grid(), ylim = c(0,4,-3,3), xlim = c(-6,6))
-##D
-##D par(mfrow=c(1,3))
-##D infoPlot(IC1, mfColRow = FALSE, panel.first= grid(),
-##D ylim = c(0,4,0,.3,0,.8), xlim=c(-6,6))
-##D par(mfrow=c(1,1))
-##D
-##D data <- r(N)(20)
-##D par(mfrow=c(1,3))
-##D infoPlot(IC1, data=data, mfColRow = FALSE, panel.first= grid(),
-##D with.lab = TRUE, cex.pts=2,
-##D which.lbs = c(1:4,15:20), which.Order = 1:6,
-##D return.Order = TRUE)
-##D infoPlot(IC1, data=data[1:10], mfColRow = FALSE, panel.first= grid(),
-##D with.lab = TRUE, cex.pts=0.7)
-##D par(mfrow=c(1,1))
-## End(Not run)
-
-
-
-
-cleanEx()
-nameEx("internals_ddPlot")
-### * internals_ddPlot
-
-flush(stderr()); flush(stdout())
-
-### Name: internals_for_RobAStBase_ddPlot
-### Title: Internal / Helper functions of package RobAStBase for ddPlot
-### Aliases: internals_for_RobAStBase_ddPlot .ddPlot.MatNtNtCoCo
-### Keywords: internal hplot
-
-### ** Examples
-
-MX <- matrix(rnorm(1500),nrow=6)
-QM <- matrix(rnorm(36),nrow=6); QM <- QM %*% t(QM)
-RobAStBase:::.ddPlot.MatNtNtCoCo(data=MX,
- dist.y=QFNorm(QuadF=PosSemDefSymmMatrix(QM)),
- xlab="Norm.x",ylab="Norm.y", cex.idn = 1.3, offset=0,
- lwd=2, lwd.cutoff=4, lty=2, col.cutoff =2, col.idn="green",
- col = "blue", adj=0.4, pos=4,id.n = sample(1:200,size=100),
- lab.pts=letters,log="x", main="GA", sub="NO",cex.sub=0.2)
-
-
-
-cleanEx()
-nameEx("interpolRisk-class")
-### * interpolRisk-class
-
-flush(stderr()); flush(stdout())
-
-### Name: interpolRisk-class
-### Title: Interpolated Risks
-### Aliases: interpolRisk-class OMSRRisk-class RMXRRisk-class MBRRisk-class
-### OMSRRisk RMXRRisk MBRRisk
-### Keywords: classes
-
-### ** Examples
-
-new("OMSRRisk")
-OMSRRisk()
-RMXRRisk()
-MBRRisk()
-myrisk <- MBRRisk(samplesize=100)
-samplesize(myrisk)
-samplesize(myrisk) <- 20
-
-
-
-cleanEx()
-nameEx("kStepEstimator")
-### * kStepEstimator
-
-flush(stderr()); flush(stdout())
-
-### Name: kStepEstimator
-### Title: Function for the computation of k-step estimates
-### Aliases: kStepEstimator
-### Keywords: univar robust
-
-### ** Examples
-
-if(require(ROptEst)){
-## 1. generate a contaminated sample
-ind <- rbinom(100, size=1, prob=0.05)
-x <- rnorm(100, mean=0, sd=(1-ind) + ind*9)
-
-## 2. Kolmogorov(-Smirnov) minimum distance estimator
-(est0 <- MDEstimator(x=x, NormLocationScaleFamily()))
-
-## 3. k-step estimation: radius known
-N1 <- NormLocationScaleFamily(mean=estimate(est0)["mean"], sd=estimate(est0)["sd"])
-N1.Rob <- InfRobModel(center = N1, neighbor = ContNeighborhood(radius = 0.5))
-IC1 <- optIC(model = N1.Rob, risk = asMSE())
-(est1 <- kStepEstimator(x, IC1, est0, steps = 3, withPIC = TRUE))
-estimate(est1)
-ksteps(est1)
-pICList(est1)
-start(est1)
-
-## don't run to reduce check time on CRAN
-## Not run:
-##D ## a transformed model
-##D tfct <- function(x){
-##D nms0 <- c("mean","sd")
-##D nms <- "comb"
-##D fval0 <- x[1]+2*x[2]
-##D names(fval0) <- nms
-##D mat0 <- matrix(c(1,2), nrow = 1, dimnames = list(nms,nms0))
-##D return(list(fval = fval0, mat = mat0))
-##D }
-##D
-##D N1.traf <- N1; trafo(N1.traf) <- tfct
-##D N1R.traf <- N1.Rob; trafo(N1R.traf) <- tfct
-##D IC1.traf <- optIC(model = N1R.traf, risk = asMSE())
-##D (est0.traf <- MDEstimator(x, N1.traf))
-##D (est1.traf <- kStepEstimator(x, IC1.traf, est0, steps = 3,
-##D withIC = TRUE, withPIC = TRUE, withUpdateInKer = FALSE))
-##D (est1a.traf <- kStepEstimator(x, IC1.traf, est0, steps = 3,
-##D withIC = TRUE, withPIC = TRUE, withUpdateInKer = TRUE))
-##D estimate(est1.traf)
-##D ksteps(est1.traf)
-##D pICList(est1.traf)
-##D startval(est1.traf)
-##D
-##D untransformed.estimate(est1.traf)
-##D uksteps(est1.traf)
-##D ICList(est1.traf)
-##D ustartval(est1.traf)
-##D
-##D estimate(est1a.traf)
-##D ksteps(est1a.traf)
-##D pICList(est1a.traf)
-##D startval(est1a.traf)
-##D
-##D untransformed.estimate(est1a.traf)
-##D uksteps(est1a.traf)
-##D ICList(est1a.traf)
-##D ustartval(est1a.traf)
-## End(Not run)
-}
-
-
-
-cleanEx()
-nameEx("makeIC-methods")
-### * makeIC-methods
-
-flush(stderr()); flush(stdout())
-
-### Name: makeIC-methods
-### Title: Generic Function for making ICs consistent at a possibly
-### different model
-### Aliases: makeIC makeIC-methods makeIC,IC,missing-method
-### makeIC,IC,L2ParamFamily-method makeIC,list,L2ParamFamily-method
-### makeIC,function,L2ParamFamily-method
-### Keywords: robust
-
-### ** Examples
-
-## default IC
-IC1 <- new("IC")
-
-## L2-differentiable parametric family
-B <- BinomFamily(13, 0.3)
-
-## check IC properties
-checkIC(IC1, B)
-
-## make IC
-IC2 <- makeIC(IC1, B)
-
-## check IC properties
-checkIC(IC2)
-
-## slot modifyIC is filled in case of IC2
-IC3 <- modifyIC(IC2)(BinomFamily(13, 0.2), IC2)
-checkIC(IC3)
-## identical to
-checkIC(IC3, BinomFamily(13, 0.2))
-
-IC4 <- makeIC(sin, B)
-checkIC(IC4)
-
-(IC5 <- makeIC(list(function(x)x^3), B, name="a try"))
-plot(IC5)
-checkIC(IC5)
-
-## don't run to reduce check time on CRAN
-## Not run:
-##D N0 <- NormLocationScaleFamily()
-##D IC6 <- makeIC(list(sin,cos),N0)
-##D plot(IC6)
-##D checkIC(IC6)
-##D
-##D getRiskIC(IC6,risk=trAsCov())$trAsCov$value
-##D getRiskIC(IC6,risk=asBias(),neighbor=ContNeighborhood())$asBias$value
-## End(Not run)
-
-
-
-
-cleanEx()
-nameEx("optIC")
-### * optIC
-
-flush(stderr()); flush(stdout())
-
-### Name: optIC
-### Title: Generic function for the computation of optimally robust ICs
-### Aliases: optIC optIC-methods optIC,L2ParamFamily,asCov-method
-### Keywords: robust
-
-### ** Examples
-
-B <- BinomFamily(size = 25, prob = 0.25)
-
-## classical optimal IC
-IC0 <- optIC(model = B, risk = asCov())
-plot(IC0) # plot IC
-checkIC(IC0, B)
-
-
-
-cleanEx()
-nameEx("outlyingPlotIC")
-### * outlyingPlotIC
-
-flush(stderr()); flush(stdout())
-
-### Name: outlyingPlotIC
-### Title: Function outlyingPlotIC in Package 'RobAStBase'
-### Aliases: outlyingPlotIC
-### Keywords: hplot
-
-### ** Examples
-
-if(require(ROptEst)){
-## generates normal location and scale family with mean = -2 and sd = 3
-N0 <- NormLocationScaleFamily()
-N0.IC0 <- optIC(model = N0, risk = asCov())
-N0.Rob1 <- InfRobModel(center = N0, neighbor = ContNeighborhood(radius = 0.5))
-N0.IC1 <- optIC(model = N0.Rob1, risk = asMSE())
-xn <- c(rnorm(100),rcauchy(20)+20)
-outlyingPlotIC(xn, IC.x=N0.IC0)
-outlyingPlotIC(xn, IC.x=N0.IC1)
-}
-
-
-
-cleanEx()
-nameEx("plot-methods")
-### * plot-methods
-
-flush(stderr()); flush(stdout())
-
-### Name: plot-methods
-### Title: Methods for Function plot in Package 'RobAStBase'
-### Aliases: plot plot-methods plot,IC,missing-method
-### plot,IC,numeric-method
-### Keywords: methods distribution
-
-### ** Examples
-
-IC1 <- new("IC")
-plot(IC1)
-plot(IC1, main = TRUE, panel.first= grid(),
- col = "blue", cex.main = 2, cex.inner = 1)
-
-### selection of subpanels for plotting
-N <- NormLocationScaleFamily(mean=0, sd=1)
-IC2 <- optIC(model = N, risk = asCov())
-par(mfrow=c(1,1))
-plot(IC2, main = TRUE, panel.first= grid(),
- col = "blue", cex.main = 2, cex.inner = 0.6,
- mfColRow = FALSE, to.draw.arg=c("sd"))
-
-## xlim and ylim arguments
-plot(IC2, main = TRUE, panel.first= grid(),
- ylim=c(-3,3), xlim=c(-2,3))
-plot(IC2, main = TRUE, panel.first= grid(),
- ylim=c(-3,3,-1,3), xlim=c(-2,3),
- with.legend = TRUE)
-
-data <- r(N)(30)
-plot(IC2, data, panel.first= grid(),
- ylim = c(-3,3,-1,3), xlim=c(-2,3),
- cex.pts = 3, pch.pts = 1:2, col.pts="green",
- with.lab = TRUE, which.lbs = c(1:4,15:20),
- which.Order = 1:6, return.Order = TRUE)
-
-
-
-graphics::par(get("par.postscript", pos = 'CheckExEnv'))
-cleanEx()
-nameEx("qqplot")
-### * qqplot
-
-flush(stderr()); flush(stdout())
-
-### Name: qqplot
-### Title: Methods for Function qqplot in Package 'RobAStBase'
-### Aliases: qqplot qqplot-methods qqplot,ANY,RobModel-method
-### qqplot,ANY,InfRobModel-method qqplot,ANY,kStepEstimate-method
-### Keywords: hplot distribution
-
-### ** Examples
-
-qqplot(r(Norm(15,sqrt(30)))(40), Chisq(df=15))
-RobM <- InfRobModel(center = NormLocationFamily(mean=13,sd=sqrt(28)),
- neighbor = ContNeighborhood(radius = 0.4))
-x <- r(Norm(15,sqrt(30)))(20)
-qqplot(x, RobM)
-qqplot(x, RobM, alpha.CI=0.9)
-## further examples for ANY,kStepEstimator-method
-## in example to roptest() in package ROptEst
-
-
-
-cleanEx()
-nameEx("samplesize-methods")
-### * samplesize-methods
-
-flush(stderr()); flush(stdout())
-
-### Name: samplesize-methods
-### Title: Methods for Function samplesize in Package 'RobAStBase'
-### Aliases: samplesize,interpolRisk-method samplesize
-### samplesize<-,interpolRisk-method samplesize<-
-### Keywords: classes
-
-### ** Examples
-
-myrisk <- MBRRisk(samplesize=100)
-samplesize(myrisk)
-samplesize(myrisk) <- 20
-
-
-
-### * <FOOTER>
-###
-cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
-grDevices::dev.off()
-###
-### Local variables: ***
-### mode: outline-minor ***
-### outline-regexp: "\\(> \\)?### [*]+" ***
-### End: ***
-quit('no')
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