[Robast-commits] r887 - in pkg/RobAStBase: R man tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Sep 1 17:48:08 CEST 2016
Author: ruckdeschel
Date: 2016-09-01 17:48:08 +0200 (Thu, 01 Sep 2016)
New Revision: 887
Added:
pkg/RobAStBase/R/getFiRisk.R
pkg/RobAStBase/R/plotUtils.R
Removed:
pkg/RobAStBase/tests/doRUnit.R
Modified:
pkg/RobAStBase/R/00internal.R
pkg/RobAStBase/R/AllGeneric.R
pkg/RobAStBase/R/AllPlot.R
pkg/RobAStBase/R/comparePlot.R
pkg/RobAStBase/R/infoPlot.R
pkg/RobAStBase/R/interpolRisks.R
pkg/RobAStBase/man/0RobAStBase-package.Rd
pkg/RobAStBase/man/comparePlot.Rd
pkg/RobAStBase/man/getRiskFctBV-methods.Rd
pkg/RobAStBase/man/infoPlot.Rd
pkg/RobAStBase/man/internals_ddPlot.Rd
pkg/RobAStBase/man/outlyingPlotIC.Rd
pkg/RobAStBase/man/plot-methods.Rd
pkg/RobAStBase/man/qqplot.Rd
Log:
trunk RobAStBase pre-release
Modified: pkg/RobAStBase/R/00internal.R
===================================================================
--- pkg/RobAStBase/R/00internal.R 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/R/00internal.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -52,6 +52,15 @@
return(wI)
}
+if(!isGeneric(".checkEstClassForParamFamily")){
+ setGeneric(".checkEstClassForParamFamily", function(PFam, estimator)
+ standardGeneric(".checkEstClassForParamFamily"))
+}
+setMethod(".checkEstClassForParamFamily",
+ signature=signature(PFam="ANY",estimator="ANY"),
+ function(PFam, estimator) estimator)
+
+
#------------------------------------------------------------------------------
### for distrXXX pre 2.5
#------------------------------------------------------------------------------
Modified: pkg/RobAStBase/R/AllGeneric.R
===================================================================
--- pkg/RobAStBase/R/AllGeneric.R 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/R/AllGeneric.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -240,3 +240,7 @@
setGeneric("rescaleFunction", function(L2Fam, ...)
standardGeneric("rescaleFunction"))
}
+if(!isGeneric("getFiRisk")){
+ setGeneric("getFiRisk",
+ function(risk, Distr, neighbor, ...) standardGeneric("getFiRisk"))
+}
Modified: pkg/RobAStBase/R/AllPlot.R
===================================================================
--- pkg/RobAStBase/R/AllPlot.R 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/R/AllPlot.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -143,7 +143,7 @@
lty <- "solid"
}else{
if(!is.null(x.vec)){
- if(is(distr, "DiscreteDistribution"))
+ if(is(e1, "DiscreteDistribution"))
x.vec <- intersect(x.vec,support(e1))
}else{
if(is(e1, "DiscreteDistribution")) x.vec <- support(e1)
Modified: pkg/RobAStBase/R/comparePlot.R
===================================================================
--- pkg/RobAStBase/R/comparePlot.R 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/R/comparePlot.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -291,8 +291,8 @@
absInfoEval <- function(x,IC){
QF <- ID
if(is(IC,"ContIC") & dims>1 ){
- if (is(normtype(object),"QFNorm"))
- QF <- QuadForm(normtype(object))
+ if (is(normtype(IC),"QFNorm"))
+ QF <- QuadForm(normtype(IC))
}
absInfo.f <- t(IC) %*% QF %*% IC
return(sapply(x, absInfo.f at Map[[1]]))
@@ -386,8 +386,8 @@
finiteEndpoints <- rep(FALSE,4)
if(scaleX){
- finiteEndpoints[1] <- is.finite(scaleX.inv(min(x.vec1, xlim[1],na.rm=TRUE)))
- finiteEndpoints[2] <- is.finite(scaleX.inv(max(x.vec1, xlim[2],na.rm=TRUE)))
+ finiteEndpoints[1] <- is.finite(scaleX.inv(min(x.vec, xlim[1],na.rm=TRUE)))
+ finiteEndpoints[2] <- is.finite(scaleX.inv(max(x.vec, xlim[2],na.rm=TRUE)))
}
if(scaleY){
finiteEndpoints[3] <- is.finite(scaleY.inv[[i]](min(ym, ylim[1,i],na.rm=TRUE)))
Added: pkg/RobAStBase/R/getFiRisk.R
===================================================================
--- pkg/RobAStBase/R/getFiRisk.R (rev 0)
+++ pkg/RobAStBase/R/getFiRisk.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -0,0 +1,196 @@
+###############################################################################
+## finite-sample under-/overshoot risk
+###############################################################################
+
+# cdf of truncated normal distribution
+ptnorm <- function(x, mu, A, B){
+ ((A <= x)*(x <= B)*(pnorm(x-mu)-pnorm(A-mu))/(pnorm(B-mu)-pnorm(A-mu))
+ + (x > B))
+}
+
+# n-fold convolution for truncated normal distributions
+conv.tnorm <- function(z, A, B, mu, n, m){
+ if(n == 1) return(ptnorm(z, mu = mu, A = A, B = B))
+ if(z <= n*A) return(0)
+ if(z >= n*B) return(1)
+
+ M <- 2^m
+ h <- (B-A)/M
+ x <- seq(from = A, to = B, by = h)
+ p1 <- ptnorm(x, mu = mu, A = A, B = B)
+ p1 <- p1[2:(M + 1)] - p1[1:M]
+
+ ## FFT
+ pn <- c(p1, numeric((n-1)*M))
+
+ ## convolution theorem for DFTs
+ pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
+ pn <- (abs(pn) >= .Machine$double.eps)*pn
+ i.max <- n*M-(n-2)
+ pn <- c(0,pn[1:i.max])
+ pn <- cumsum(pn)
+
+ ## cdf with continuity correction h/2
+ x <- c(n*A,seq(from = n*A+n/2*h, to = n*B-n/2*h, by=h),n*B)
+ pnfun1 <- approxfun(x = x+0.5*h, y = pn, yleft = 0, yright = pn[i.max+1])
+ pnfun2 <- function(x) pnfun1(x) / pn[i.max+1]
+
+ return(pnfun2(z))
+}
+
+
+setMethod("getFiRisk", signature(risk = "fiUnOvShoot",
+ Distr = "Norm",
+ neighbor = "ContNeighborhood"),
+ function(risk, Distr, neighbor, clip, stand, sampleSize, Algo, cont){
+ eps <- neighbor at radius
+ tau <- risk at width
+ n <- sampleSize
+ m <- getdistrOption("DefaultNrFFTGridPointsExponent")
+
+ if(Algo == "B"){
+ if(cont == "left"){
+ delta1 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
+ K1 <- dbinom(0:n, size = n, prob = delta1)
+ P1 <- (1-eps)*pnorm(-clip-tau) + eps
+ p1 <- P1/delta1
+
+ summe1 <- numeric(n+1)
+ summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
+ summe1[n+1] <- (1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
+ + pbinom(q = n/2-0.1, size = n, prob = p1)))
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
+ summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
+ }
+ erg <- sum(summe1*K1)
+ }else{
+ delta2 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
+ K2 <- dbinom(0:n, size = n, prob = delta2)
+ P2 <- (1-eps)*pnorm(-clip+tau)
+ p2 <- P2/delta2
+
+ summe2 <- numeric(n+1)
+ summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
+ summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
+ + pbinom(q = n/2-0.1, size = n, prob = p2))
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
+ summe2[k+1] <- sum(P2.ste*dbinom(j, size=k, prob=p2))
+ }
+ erg <- sum(summe2*K2)
+ }
+ }else{
+ M <- 2^m
+ h <- 2*clip/M
+ x <- seq(from = -clip, to = clip, by = h)
+
+ if(cont == "right"){
+ p1 <- pnorm(x+tau)
+ p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
+ p1[1] <- p1[1] + (1-eps)*pnorm(-clip+tau)
+ p1[M] <- p1[M] + (1-eps)*pnorm(-clip-tau) + eps
+ }else{
+ p1 <- pnorm(x-tau)
+ p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
+ p1[1] <- p1[1] + (1-eps)*pnorm(-clip-tau) + eps
+ p1[M] <- p1[M] + (1-eps)*pnorm(-clip+tau)
+ }
+
+ ## FFT
+ pn <- c(p1, numeric((n-1)*M))
+
+ ## convolution theorem for DFTs
+ pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
+ pn <- (abs(pn) >= .Machine$double.eps)*pn
+ pn <- cumsum(pn)
+
+ k <- n*(M-1)/2
+ erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
+ if(cont == "right") erg <- 1 - erg
+ }
+
+ return(list(fiUnOvShoot = erg))
+ })
+
+setMethod("getFiRisk", signature(risk = "fiUnOvShoot",
+ Distr = "Norm",
+ neighbor = "TotalVarNeighborhood"),
+ function(risk, Distr, neighbor, clip, stand, sampleSize, Algo, cont){
+ delta <- neighbor at radius
+ tau <- risk at width
+ n <- sampleSize
+ m <- getdistrOption("DefaultNrFFTGridPointsExponent")
+
+ if(Algo == "B"){
+ if(cont == "left"){
+ delta1 <- min(pnorm(-clip-tau)+delta, 1) + 1 - min(pnorm(clip-tau)+delta, 1)
+ K1 <- dbinom(0:n, size = n, prob = delta1)
+ P1 <- min(pnorm(-clip-tau) + delta, 1)
+ p1 <- min(P1/delta1, 1)
+
+ summe1 <- numeric(n+1)
+ summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
+ summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
+ }
+ summe1[n+1] <- 1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
+ + pbinom(q = n/2-0.1, size = n, prob = p1))
+ erg <- sum(summe1*K1)
+ }else{
+ delta2 <- max(0, pnorm(-clip+tau)-delta) + 1 - max(0, pnorm(clip+tau)-delta)
+ K2 <- dbinom(0:n, size = n, prob = delta2)
+ P2 <- max(0, pnorm(-clip+tau) - delta)
+ p2 <- P2/delta2
+
+ summe2 <- numeric(n+1)
+ summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
+ for(k in 1:(n-1)){
+ j <- 0:k
+ z <- clip*(k-2*j)
+ P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
+ summe2[k+1] <- sum(P2.ste*dbinom(j, size = k, prob = p2))
+ }
+ summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
+ + pbinom(q = n/2-0.1, size = n, prob = p2))
+ erg <- sum(summe2*K2)
+ }
+ }else{
+ M <- 2^m
+ h <- 2*clip/M
+ x <- seq(from = -clip, to = clip, by = h)
+
+ if(cont == "right"){
+ p1 <- pnorm(x+tau)
+ p1 <- p1[2:(M + 1)] - p1[1:M]
+ p1[1] <- p1[1] + pnorm(-clip+tau) - delta
+ p1[M] <- p1[M] + pnorm(-clip-tau) + delta
+ }else{
+ p1 <- pnorm(x-tau)
+ p1 <- p1[2:(M + 1)] - p1[1:M]
+ p1[1] <- p1[1] + pnorm(-clip-tau) + delta
+ p1[M] <- p1[M] + pnorm(-clip+tau) - delta
+ }
+
+ ## FFT
+ pn <- c(p1, numeric((n-1)*M))
+
+ ## convolution theorem for DFTs
+ pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
+ pn <- (abs(pn) >= .Machine$double.eps)*pn
+ pn <- cumsum(pn)
+
+ k <- n*(M-1)/2
+ erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
+ if(cont == "right") erg <- 1-erg
+ }
+
+ return(list(fiUnOvShoot = erg))
+ })
Modified: pkg/RobAStBase/R/infoPlot.R
===================================================================
--- pkg/RobAStBase/R/infoPlot.R 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/R/infoPlot.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -129,9 +129,9 @@
if(is(distr, "DiscreteDistribution"))
x.vec <- intersect(x.vec,support(distr))
}else{
- if(is(e1, "DiscreteDistribution")) x.vec <- support(distr)
+ if(is(distr, "DiscreteDistribution")) x.vec <- support(distr)
else{
- x.vec <- r(e1)(1000)
+ x.vec <- r(distr)(1000)
x.vec <- sort(unique(x.vec))
}
}
@@ -587,8 +587,8 @@
finiteEndpoints[2] <- is.finite(scaleX.inv(max(resc$X, xlim[2],na.rm=TRUE)))
}
if(scaleY){
- finiteEndpoints[3] <- is.finite(scaleY.inv[[i+in1to.draw]](min(yvec1, ylim[1,i+in1to.draw],na.rm=TRUE)))
- finiteEndpoints[4] <- is.finite(scaleY.inv[[i+in1to.draw]](max(yvec1, ylim[2,i+in1to.draw],na.rm=TRUE)))
+ finiteEndpoints[3] <- is.finite(scaleY.inv[[i+in1to.draw]](min(y.vec1, ylim[1,i+in1to.draw],na.rm=TRUE)))
+ finiteEndpoints[4] <- is.finite(scaleY.inv[[i+in1to.draw]](max(y.vec1, ylim[2,i+in1to.draw],na.rm=TRUE)))
}
.plotRescaledAxis(scaleX0, scaleX.fct, scaleX.inv,
Modified: pkg/RobAStBase/R/interpolRisks.R
===================================================================
--- pkg/RobAStBase/R/interpolRisks.R 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/R/interpolRisks.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -5,3 +5,5 @@
setMethod("samplesize","interpolRisk", function(object)object at samplesize)
setReplaceMethod("samplesize","interpolRisk", function(object, value){
object at samplesize <- value; object})
+setMethod("biastype","interpolRisk", function(object) symmetricBias())
+setMethod("normtype","interpolRisk", function(object) NormType())
Added: pkg/RobAStBase/R/plotUtils.R
===================================================================
--- pkg/RobAStBase/R/plotUtils.R (rev 0)
+++ pkg/RobAStBase/R/plotUtils.R 2016-09-01 15:48:08 UTC (rev 887)
@@ -0,0 +1,10 @@
+ .cexscale <- function(y, y1=y, maxcex=4,mincex=0.05,cex, fun=NULL){
+ if(is.null(fun)) fun <- function(x) log(1+abs(x))
+ ly <- fun(y)
+ ly1 <- fun(unique(c(y,y1)))
+ my <- min(ly1,na.rm=TRUE)
+ My <- max(ly1,na.rm=TRUE)
+ ly0 <- (ly-my)/My
+ ly1 <- ly0*(maxcex-mincex)+mincex
+ return(cex*ly1)
+ }
Modified: pkg/RobAStBase/man/0RobAStBase-package.Rd
===================================================================
--- pkg/RobAStBase/man/0RobAStBase-package.Rd 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/man/0RobAStBase-package.Rd 2016-09-01 15:48:08 UTC (rev 887)
@@ -12,14 +12,15 @@
\tabular{ll}{
Package: \tab RobAStBase \cr
Version: \tab 1.0 \cr
-Date: \tab 2015-05-03 \cr
-Depends: \tab R(>= 2.14.0), methods, rrcov, distr(>= 2.5.2), distrEx(>= 2.5), distrMod(>= 2.5.2), RandVar(>= 0.9.2)\cr
+Date: \tab 2016-09-01 \cr
+Depends: \tab R(>= 2.14.0), methods, rrcov, distr(>= 2.5.2), distrEx(>= 2.5), distrMod(>= 2.5.2),
+RandVar(>= 0.9.2) \cr
Suggests: \tab ROptEst, RUnit (>= 0.4.26)\cr
Imports: \tab startupmsg\cr
ByteCompile: \tab yes \cr
License: \tab LGPL-3 \cr
URL: \tab http://robast.r-forge.r-project.org/\cr
-SVNRevision: \tab 694 \cr
+SVNRevision: \tab 874 \cr
}
}
\author{
Modified: pkg/RobAStBase/man/comparePlot.Rd
===================================================================
--- pkg/RobAStBase/man/comparePlot.Rd 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/man/comparePlot.Rd 2016-09-01 15:48:08 UTC (rev 887)
@@ -10,28 +10,25 @@
}
\usage{
comparePlot(obj1, obj2, ... )
-\S4method{comparePlot}{IC,IC}(obj1, obj2, obj3 = NULL, obj4 = NULL,
- data = NULL, ..., withSweave = getdistrOption("withSweave"),
- forceSameModel = FALSE,
- main = FALSE, inner = TRUE, sub = FALSE,
- col = par("col"), lwd = par("lwd"), lty,
- col.inner = par("col.main"), cex.inner = 0.8,
- bmar = par("mar")[1], tmar = par("mar")[3],
- with.automatic.grid = TRUE,
- with.legend = FALSE, legend = NULL, legend.bg = "white",
- legend.location = "bottomright", legend.cex = 0.8,
- withMBR = FALSE, MBRB = NA, MBR.fac = 2, col.MBR = par("col"),
- lty.MBR = "dashed", lwd.MBR = 0.8,
- x.vec = NULL, scaleX = FALSE, scaleX.fct, scaleX.inv,
- scaleY = FALSE, scaleY.fct = pnorm, scaleY.inv=qnorm,
- scaleN = 9, x.ticks = NULL, y.ticks = NULL,
- mfColRow = TRUE, to.draw.arg = NULL,
- cex.pts = 1, cex.pts.fun = NULL, col.pts = par("col"),
- pch.pts = 1, jit.fac = 1, jit.tol = .Machine$double.eps, with.lab = FALSE,
- lab.pts = NULL, lab.font = NULL, alpha.trsp = NA,
- which.lbs = NULL, which.Order = NULL, return.Order = FALSE,
- draw.nonlbl = TRUE, cex.nonlbl=0.3, pch.nonlbl=".",
- withSubst = TRUE)
+\S4method{comparePlot}{IC,IC}(obj1, obj2, obj3 = NULL, obj4 = NULL, data = NULL,
+ ..., withSweave = getdistrOption("withSweave"),
+ forceSameModel = FALSE, main = FALSE, inner = TRUE,
+ sub = FALSE, col = par("col"), lwd = par("lwd"), lty,
+ col.inner = par("col.main"), cex.inner = 0.8, bmar =
+ par("mar")[1], tmar = par("mar")[3],
+ with.automatic.grid = TRUE, with.legend = FALSE,
+ legend = NULL, legend.bg = "white", legend.location =
+ "bottomright", legend.cex = 0.8, withMBR = FALSE, MBRB
+ = NA, MBR.fac = 2, col.MBR = par("col"), lty.MBR =
+ "dashed", lwd.MBR = 0.8, x.vec = NULL, scaleX = FALSE,
+ scaleX.fct, scaleX.inv, scaleY = FALSE, scaleY.fct =
+ pnorm, scaleY.inv = qnorm, scaleN = 9, x.ticks = NULL,
+ y.ticks = NULL, mfColRow = TRUE, to.draw.arg = NULL,
+ cex.pts = 1, cex.pts.fun = NULL, col.pts = par("col"),
+ pch.pts = 1, jitter.fac = 1, with.lab = FALSE, lab.pts
+ = NULL, lab.font = NULL, alpha.trsp = NA, which.lbs =
+ NULL, which.Order = NULL, return.Order = FALSE,
+ withSubst = TRUE)
}
\arguments{
\item{obj1}{ object of class \code{"InfluenceCurve"} }
@@ -138,21 +135,37 @@
}
\item{withSubst}{logical; if \code{TRUE} (default) pattern substitution for
titles and lables is used; otherwise no substitution is used. }
- \item{cex.pts}{size of the points of the \code{data} argument plotted}
+ \item{col.pts}{color of the points of the \code{data} argument plotted; (may
+ be a vector of length \code{nIC}, \code{nIC} the number of plotted pICs,
+ i.e., one value for each pIC in arguments \code{obj1}, \code{obj2}, and,
+ if available, \code{obj3} and \code{obj4}, or it can be a matrix
+ \code{n} by \code{nIC}, \code{n} the number of observations prior to any
+ selection, in which case it assigns observation-specific colors to the
+ observations; in this case this overrides settings in the respective
+ \code{col.nonlbl} argument.}
+ \item{pch.pts}{symbol of the points of the \code{data} argument plotted
+ (may be a vector of length \code{nIC} or a matrix, see \code{col.pts}).}
+ \item{cex.pts}{size of the points of the \code{data} argument plotted
+ (may be a vector of length \code{nIC} or a matrix, see \code{col.pts}).}
\item{cex.pts.fun}{rescaling function for the size of the points to be plotted;
either \code{NULL} (default), then \code{log(1+abs(x))} is used for each of
the rescalings, or a function which is then used for each of the
rescalings, or a list of functions; if it is a function or a list of
functions, if necessary it is recylced to length \code{nIC * dim}
- where \code{nIC} is the number of pICs and \code{dim} is the number of
- dimensions of the pICs to be plotted; in the index of this list,
- \code{nIC} is incremented first; then \code{dim}.}
- \item{col.pts}{color of the points of the \code{data} argument plotted}
- \item{pch.pts}{symbol of the points of the \code{data} argument plotted}
- \item{with.lab}{logical; shall labels be plotted to the observations?}
- \item{lab.pts}{character or NULL; labels to be plotted to the observations; if \code{NULL}
- observation indices;}
- \item{lab.font}{font to be used for labels}
+ where \code{dim} is the number of dimensions of the pICs to be plotted;
+ in the index of this list, \code{nIC} is incremented first;
+ then \code{dim}.}
+
+ \item{with.lab}{logical; shall labels be plotted to the observations?
+ (May be a vector of length \code{nIC}, see \code{col.pts}
+ -- but not a matrix).}
+ \item{lab.pts}{character or NULL; labels to be plotted to the observations;
+ can be a vector of length \code{n}, \code{n} the number of
+ all observations prior to any selection with \code{which.lbs},
+ \code{which.Order}; if \code{lab.pts} is \code{NULL},
+ observation indices are used.}
+ \item{lab.font}{font to be used for labels (may be a vector of length
+ \code{nIC}, see \code{with.lab}).}
\item{alpha.trsp}{alpha transparency to be added ex post to colors
\code{col.pch} and \code{col.lbl}; if one-dim and NA all colors are
left unchanged. Otherwise, with usual recycling rules \code{alpha.trsp}
@@ -161,12 +174,11 @@
while for the remaining ones, the alpha channel in rgb space is set
to the respective coordinate value of \code{alpha.trsp}. The non-NA
entries must be integers in [0,255] (0 invisible, 255 opaque).}
- \item{jit.fac}{jittering factor used in case of a \code{DiscreteDistribution}
- for plotting points of the \code{data} argument in a jittered fashion.}
- \item{jit.tol}{threshold for jittering: if distance between points is smaller
- than \code{jit.tol}, points are considered replicates.}
+ \item{jitter.fac}{jittering factor used in case of a \code{DiscreteDistribution}
+ for plotting points of the \code{data} argument in a jittered
+ fashion (may be a vector of length 2, see \code{with.lab}).}
\item{which.lbs}{either an integer vector with the indices of the observations
- to be plotted into graph or \code{NULL} --- then no observation is excluded}
+ to be plotted into graph or \code{NULL} --- then no observation is excluded.}
\item{which.Order}{for each of the given ICs, we order the observations (descending)
according to the norm given by the corresponding \code{normtype(object)};
then \code{which.Order} either is an integer vector with the indices of the \emph{ordered}
@@ -180,11 +192,14 @@
reduction by argument \code{which.lbs}, and ordering is according to the norm given by
\code{normtype(object)});
othervise we return \code{invisible()} as usual.}
- \item{draw.nonlbl}{logical; should non-labelled observations be drawn?}
- \item{cex.nonlbl}{character expansion(s) for non-labelled observations}
- \item{pch.nonlbl}{plotting symbol(s) for non-labelled observations}
\item{\dots}{further arguments to be passed to \code{plot}}
}
+\value{
+ The function returns invisibly a list of elements containing the information
+ needed to compute the respective diagnostic plot.
+ The return value allows to recover all information used to produce the plot
+ for later use in enhanced graphics (e.g. with ggplot).
+}
\details{
Any parameters of \code{plot.default} may be passed on to this particular
\code{plot} method.
Modified: pkg/RobAStBase/man/getRiskFctBV-methods.Rd
===================================================================
--- pkg/RobAStBase/man/getRiskFctBV-methods.Rd 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/man/getRiskFctBV-methods.Rd 2016-09-01 15:48:08 UTC (rev 887)
@@ -4,6 +4,7 @@
\alias{getRiskFctBV-methods}
\alias{getRiskFctBV,asGRisk,ANY-method}
\alias{getRiskFctBV,asMSE,ANY-method}
+\alias{getRiskFctBV,interpolRisk,ANY-method}
\alias{getRiskFctBV,asSemivar,onesidedBias-method}
\alias{getRiskFctBV,asSemivar,asymmetricBias-method}
\title{Methods for Function getRiskFctBV in Package `RobAStBase'}
Modified: pkg/RobAStBase/man/infoPlot.Rd
===================================================================
--- pkg/RobAStBase/man/infoPlot.Rd 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/man/infoPlot.Rd 2016-09-01 15:48:08 UTC (rev 887)
@@ -9,28 +9,20 @@
}
\usage{
infoPlot(object, ...)
-\S4method{infoPlot}{IC}(object, data = NULL, ...,
- withSweave = getdistrOption("withSweave"),
- col = par("col"), lwd = par("lwd"), lty,
- colI = grey(0.5), lwdI = 0.7*par("lwd"), ltyI = "dotted",
- main = FALSE, inner = TRUE, sub = FALSE,
- col.inner = par("col.main"), cex.inner = 0.8,
- bmar = par("mar")[1], tmar = par("mar")[3],
- with.automatic.grid = TRUE,
- with.legend = TRUE, legend = NULL, legend.bg = "white",
- legend.location = "bottomright", legend.cex = 0.8,
- x.vec = NULL, scaleX = FALSE, scaleX.fct, scaleX.inv,
- scaleY = FALSE, scaleY.fct = pnorm, scaleY.inv=qnorm,
- scaleN = 9, x.ticks = NULL, y.ticks = NULL,
- mfColRow = TRUE, to.draw.arg = NULL,
- cex.pts = 1, cex.pts.fun = NULL, col.pts = par("col"),
- pch.pts = 1, jit.fac = 1, jit.tol = .Machine$double.eps, with.lab = FALSE,
- lab.pts = NULL, lab.font = NULL, alpha.trsp = NA,
- which.lbs = NULL, which.Order = NULL, return.Order = FALSE,
- draw.nonlbl = TRUE, cex.nonlbl=0.3, pch.nonlbl=".",
- ylab.abs = "absolute information",
- ylab.rel= "relative information",
- withSubst = TRUE)
+\S4method{infoPlot}{IC}(object, data = NULL, ...,
+withSweave = getdistrOption("withSweave"), col = par("col"), lwd = par("lwd"),
+lty, colI = grey(0.5), lwdI = 0.7 * par("lwd"), ltyI = "dotted", main = FALSE,
+inner = TRUE, sub = FALSE, col.inner = par("col.main"), cex.inner = 0.8,
+bmar = par("mar")[1], tmar = par("mar")[3], with.automatic.grid = TRUE,
+with.legend = TRUE, legend = NULL, legend.bg = "white",
+ legend.location = "bottomright", legend.cex = 0.8, x.vec = NULL,
+ scaleX = FALSE, scaleX.fct, scaleX.inv,scaleY = FALSE, scaleY.fct = pnorm,
+ scaleY.inv = qnorm, scaleN = 9, x.ticks = NULL, y.ticks = NULL,
+ mfColRow = TRUE, to.draw.arg = NULL, cex.pts = 1, cex.pts.fun = NULL,
+ col.pts = par("col"), pch.pts = 1, jitter.fac = 1, with.lab = FALSE,
+ lab.pts = NULL, lab.font = NULL, alpha.trsp = NA, which.lbs = NULL,
+ which.Order = NULL, return.Order = FALSE, ylab.abs = "absolute information",
+ ylab.rel = "relative information", withSubst = TRUE)
}
\arguments{
\item{object}{object of class \code{"InfluenceCurve"} }
@@ -134,7 +126,16 @@
}
\item{withSubst}{logical; if \code{TRUE} (default) pattern substitution for
titles and lables is used; otherwise no substitution is used. }
- \item{cex.pts}{size of the points of the \code{data} argument plotted}
+ \item{col.pts}{color of the points of the \code{data} argument plotted; (may
+ be a vector of length 2, one value for the classical IC, one for the IC
+ in argument \code{object}, or it can be a matrix \code{n} by 2, \code{n} the
+ number of observations prior to any selection, in which case it assigns
+ observation-specific colors to the observations; in this case this
+ overrides settings in the respective \code{col.nonlbl} argument.}
+ \item{pch.pts}{symbol of the points of the \code{data} argument plotted
+ (may be a vector of length 2 or a matrix, see \code{col.pts}).}
+ \item{cex.pts}{size of the points of the \code{data} argument plotted
+ (may be a vector of length 2 or a matrix, see \code{col.pts}).}
\item{cex.pts.fun}{rescaling function for the size of the points to be plotted;
either \code{NULL} (default), then \code{log(1+abs(x))} is used for each of
the rescalings, or a function which is then used for each of the
@@ -145,24 +146,27 @@
dimensions of the pICs to be plotted; in the index of this list,
the index for classical vs. \code{IC} is incremented first;
then \code{dim}.}
- \item{col.pts}{color of the points of the \code{data} argument plotted}
- \item{pch.pts}{symbol of the points of the \code{data} argument plotted}
- \item{with.lab}{logical; shall labels be plotted to the observations?}
- \item{lab.pts}{character or NULL; labels to be plotted to the observations; if \code{NULL}
- observation indices;}
- \item{lab.font}{font to be used for labels}
+ \item{with.lab}{logical; shall labels be plotted to the observations?
+ (may be a vector of length 2, see \code{col.pts} --
+ but not a matrix)}
+ \item{lab.pts}{character or NULL; labels to be plotted to the observations;
+ can be a vector of length \code{n}, \code{n} the number of
+ all observations prior to any selection with \code{which.lbs},
+ \code{which.Order}; if \code{lab.pts} is \code{NULL},
+ observation indices are used.}
+ \item{lab.font}{font to be used for labels; (may be a vector of length 2,
+ see \code{with.lab}).}
\item{alpha.trsp}{alpha transparency to be added ex post to colors
- \code{col.pch} and \code{col.lbl}; if one-dim and NA all colors are
+ \code{col.pch} and \code{col.nonlbl}; if one-dim and NA all colors are
left unchanged. Otherwise, with usual recycling rules \code{alpha.trsp}
- gets shorted/prolongated to length the data-symbols to be plotted.
- Coordinates of this vector \code{alpha.trsp} with NA are left unchanged,
+ gets shorted/prolongated to length the number of panel data-symbols to
+ be plotted. Coordinates of this vector \code{alpha.trsp} with NA are left unchanged,
while for the remaining ones, the alpha channel in rgb space is set
to the respective coordinate value of \code{alpha.trsp}. The non-NA
entries must be integers in [0,255] (0 invisible, 255 opaque).}
- \item{jit.fac}{jittering factor used in case of a \code{DiscreteDistribution}
- for plotting points of the \code{data} argument in a jittered fashion.}
- \item{jit.tol}{threshold for jittering: if distance between points is smaller
- than \code{jit.tol}, points are considered replicates.}
+ \item{jitter.fac}{jittering factor used in case of a \code{DiscreteDistribution}
+ for plotting points of the \code{data} argument in a jittered fashion
+ (may be a vector of length 2, see \code{with.lab}).}
\item{which.lbs}{either an integer vector with the indices of the observations
to be plotted into graph or \code{NULL} --- then no observation is excluded}
\item{which.Order}{we order the observations (descending) according to the norm given by
@@ -178,13 +182,16 @@
reduction by argument \code{which.lbs}, and ordering is according to the norm given by
\code{normtype(object)});
otherwise we return \code{invisible()} as usual.}
- \item{draw.nonlbl}{logical; should non-labelled observations be drawn?}
- \item{cex.nonlbl}{character expansion(s) for non-labelled observations}
- \item{pch.nonlbl}{plotting symbol(s) for non-labelled observations}
\item{ylab.abs}{character; label to be used for y-axis in absolute information panel}
\item{ylab.rel}{character; label to be used for y-axis in relative information panel}
\item{\dots}{further parameters for \code{plot}}
}
+\value{
+ The function returns invisibly a list of elements containing the information
+ needed to compute the respective diagnostic plot.
+ The return value allows to recover all information used to produce the plot
+ for later use in enhanced graphics (e.g. with ggplot).
+}
\details{
Absolute information is defined as the square of the length
of an IC. The relative information is defined as the
Modified: pkg/RobAStBase/man/internals_ddPlot.Rd
===================================================================
--- pkg/RobAStBase/man/internals_ddPlot.Rd 2016-09-01 14:13:04 UTC (rev 886)
+++ pkg/RobAStBase/man/internals_ddPlot.Rd 2016-09-01 15:48:08 UTC (rev 887)
@@ -8,22 +8,19 @@
This function is an internally used helper function for \code{\link{ddPlot}} in package \pkg{RobAStBase}.}
\usage{
-.ddPlot.MatNtNtCoCo(data, ..., dist.x = NormType(), dist.y = NormType(),
- cutoff.x = cutoff(norm = dist.x, cutoff.quantile = cutoff.quantile.x),
- cutoff.y = cutoff(norm = dist.y, cutoff.quantile = cutoff.quantile.y),
- cutoff.quantile.x = 0.95, cutoff.quantile.y = cutoff.quantile.x,
- transform.x, transform.y = transform.x,
- id.n, cex.pts = 1,lab.pts, jit.pts = 0, alpha.trsp = NA, adj =0, cex.idn,
- col.idn, lty.cutoff,
- lwd.cutoff, col.cutoff = "red", text.abline = TRUE,
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/robast -r 887
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