[Distr-commits] r1105 - in pkg/distrMod: . R man tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sat Apr 23 20:08:55 CEST 2016
Author: ruckdeschel
Date: 2016-04-23 20:08:54 +0200 (Sat, 23 Apr 2016)
New Revision: 1105
Removed:
pkg/distrMod/man/internalmdeHelpers.Rd
Modified:
pkg/distrMod/DESCRIPTION
pkg/distrMod/R/0distrModUtils.R
pkg/distrMod/R/qqplot.R
pkg/distrMod/man/0distrMod-package.Rd
pkg/distrMod/man/internals.Rd
pkg/distrMod/man/qqplot.Rd
pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save
Log:
first attempt to get distrMod on CRAN
Modified: pkg/distrMod/DESCRIPTION
===================================================================
--- pkg/distrMod/DESCRIPTION 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/DESCRIPTION 2016-04-23 18:08:54 UTC (rev 1105)
@@ -1,6 +1,6 @@
Package: distrMod
Version: 2.6
-Date: 2015-11-07
+Date: 2016-04-23
Title: Object Oriented Implementation of Probability Models
Description: Implements S4 classes for probability models based on packages 'distr' and
'distrEx'.
@@ -17,4 +17,4 @@
URL: http://distr.r-forge.r-project.org/
LastChangedDate: {$LastChangedDate$}
LastChangedRevision: {$LastChangedRevision$}
-SVNRevision: 1080
+SVNRevision: 1104
Modified: pkg/distrMod/R/0distrModUtils.R
===================================================================
--- pkg/distrMod/R/0distrModUtils.R 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/R/0distrModUtils.R 2016-04-23 18:08:54 UTC (rev 1105)
@@ -106,56 +106,66 @@
## shift L2family to a parameter value as given in main(param)
param0 <- L2Fam at param
dim0 <- dimension(param0)
-# print(param0)
paramP <- param0
paramP at main <- main(param)
paramP at trafo <- diag(dim0)
-# print(paramP)
L2Fam <- modifyModel(L2Fam, paramP)
-# print(L2deriv(L2Fam)[[1]]@Map)
distr <- L2Fam at distribution
### get a sensible integration range:
- low0 <- q(distr)(TruncQuantile)
- up0 <- q(distr)(TruncQuantile, lower.tail = FALSE)
- m0 <- median(distr); s0 <- IQR(distr)
- low1 <- m0 - IQR.fac * s0
- up1 <- m0 + IQR.fac * s0
- low <- max(low0,low1); up <- min(up0,up1)
-
+ if(is(distr,"DiscreteDistribution")){
+ x.seq0 <- x.seq <- support(distr)
+ low <- min(x.seq)
+ up <- max(x.seq)
+ }else{
### get a sensible integration range:
- if(missing(mu)) mu <- distr
- low0.mu <- q(mu)(TruncQuantile)
- up0.mu <- q(mu)(TruncQuantile, lower.tail = FALSE)
- m0.mu <- median(mu); s0.mu <- IQR(mu)
- low1.mu <- m0.mu - IQR.fac * s0.mu
- up1.mu <- m0.mu + IQR.fac * s0.mu
- low.mu <- max(low0.mu,low1.mu); up.mu <- min(up0.mu,up1.mu)
+ low0 <- q(distr)(TruncQuantile)
+ up0 <- q(distr)(TruncQuantile, lower.tail = FALSE)
+ m0 <- median(distr); s0 <- IQR(distr)
+ low1 <- m0 - IQR.fac * s0
+ up1 <- m0 + IQR.fac * s0
+ low <- max(low0,low1); up <- min(up0,up1)
+ if(is(distr,"AbscontDistribution")){
+ x.seq0 <- seq(low, up, length = N1)
+ h0 <- x.seq0[1:2]%*%c(-1,1)
+ x.seq <- x.seq0[odd]
+ }else{
+ x.seq0 <- x.seq <- seq(low,up, length = N)
+ }
+ }
-
- if(is(distr,"DiscreteDistribution"))
- x.seq <-support(distr)
- else
- {if(is(distr,"AbscontDistribution")){
- x.seq0 <- seq(low, up, length = N1)
- h0 <- x.seq0[1:2]%*%c(-1,1)
- x.seq <- x.seq0[odd]
- }else{
- x.seq <- seq(low,up, length = N)
- }
- }
- if(is(mu,"DiscreteDistribution"))
+ ## similar for mu
+ if(missing(mu)){
+ mu <- distr
+ low.mu <- low
+ up.mu <- up
+ x.mu.seq <- x.seq
+ if(is(distr,"AbscontDistribution")){
+ x.mu.seq0 <- x.seq0
+ h0.mu <- h0
+ }
+ }else{
+ if(is(distr,"DiscreteDistribution")){
x.mu.seq <- support(mu)
- else
- {if(is(mu,"AbscontDistribution")){
+ low.mu <- min(x.mu.seq)
+ up.mu <- max(x.mu.seq)
+ }else{
+ low0.mu <- q(mu)(TruncQuantile)
+ up0.mu <- q(mu)(TruncQuantile, lower.tail = FALSE)
+ m0.mu <- median(mu); s0.mu <- IQR(mu)
+ low1.mu <- m0.mu - IQR.fac * s0.mu
+ up1.mu <- m0.mu + IQR.fac * s0.mu
+ low.mu <- max(low0.mu,low1.mu); up.mu <- min(up0.mu,up1.mu)
+ if(is(mu,"AbscontDistribution")){
x.mu.seq0 <- seq(low.mu, up.mu, length = N1)
h0.mu <- x.mu.seq0[1:2]%*%c(-1,1)
x.mu.seq <- x.mu.seq0[odd]
- }else{
+ }else{
x.mu.seq <- seq(low.mu, up.mu, length = N)
- }
}
+ }
+ }
L2deriv <- L2deriv(L2Fam)[[1]]
# y.seq <- sapply(x.seq, function(x) evalRandVar(L2deriv, x))
@@ -178,30 +188,35 @@
d(distr)(x.seq0)
Delta0 <- h0*.csimpsum(Delta0x)
}else{
- L2x <- function(x,y) (x<=y)*evalRandVar(L2deriv, x)
- Delta0 <- sapply(x.seq, function(Y){ fct <- function(x) L2x(x,y=Y)
+ if(is(distr,"DiscreteDistribution")){
+ Delta0x <- sapply(x.seq0, function(x)
+ evalRandVar(L2deriv, x)) *
+ d(distr)(x.seq0)
+ Delta0 <- cumsum(Delta0x)
+ }else{
+ L2x <- function(x,y) (x<=y)*evalRandVar(L2deriv, x)
+ Delta0 <- sapply(x.seq, function(Y){ fct <- function(x) L2x(x,y=Y)
return(E(object=distr, fun = fct))})
+ }
}
# print(Delta0)
Delta1 <- approxfun(x.seq, Delta0, yleft = 0, yright = 0)
if(is(distr,"DiscreteDistribution"))
Delta <- function(x) Delta1(x) * (x %in% support(distr))
- else Delta <- function(x) Delta1(x)
- # print(Delta(x.seq))
+ else Delta <- Delta1
+# print(Delta(x.seq))
# print(Delta(rnorm(100)))
## J = Var_Ptheta Delta
- J1 <- E(object=distr, fun = Delta)
# print(J1)
- Delta.0 <- function(x) Delta(x) - J1
# print(Delta.0(x.seq))
# print(Delta.0(r(distr)(100))^2)
#J <- distrExIntegrate(function(x) d(distr)(x)*Delta.0(x)^2, lower=low, upper=up)
- J <- E(object=distr, fun = function(x) Delta.0(x)^2 )
+ J <- E(object=distr, fun = function(x) Delta(x)^2 )
# print(J)
### CvM-IC phi
- phi <- function(x) Delta.0(x)/J
+ phi <- function(x) Delta(x)/J
## integrand phi x Ptheta in formula (51) [ibid]
phi1 <- function(x) phi(x) * p(distr)(x)
@@ -236,13 +251,14 @@
psi.01 <- function(x) psi.0(x)/E3
if(withplot)
{ dev.new() #windows()
+
plot(x.seq, psi.01(x.seq),
type = if(is(distr,"DiscreteDistribution")) "p" else "l")
}
E4 <- E(object=distr, fun = function(x) psi.01(x)^2)
psi.01 <- EuclRandVariable(Map = list(psi.01), Domain = Reals())
-# print(list(E2,E4,E2-E4))
+# print(list(E1,E2,E4,E2-E4))
}else{
@@ -380,7 +396,7 @@
B0 <- BinomFamily(size=8, prob=0.3);.CvMMDCovariance(B0,par=ParamFamParameter("",.3), withplot=TRUE)
N0 <- NormLocationFamily();.CvMMDCovariance(N0,par=ParamFamParameter("",0), withplot=TRUE, N = 200)
C0 <- L2LocationFamily(central=Cauchy());.CvMMDCovariance(C0,par=ParamFamParameter("",0), withplot=TRUE, N = 200)
-N1 <- NormScaleFamily(); re=.CvMMDCovariance(N1,par=ParamFamParameter("",1), withICwithplot=TRUE, N = 200)
+N1 <- NormScaleFamily(); re=.CvMMDCovariance(N1,par=ParamFamParameter("",1), withpreIC,withplot=TRUE, N = 200)
NS <- NormLocationScaleFamily();paramP <- ParamFamParameter(name = "locscale", main = c("loc"=0,"scale"=1),trafo = diag(2));
.CvMMDCovariance(NS,par=paramP, withplot=TRUE, N = 100)
cls <- CauchyLocationScaleFamily();.CvMMDCovariance(cls,par=ParamFamParameter("",0:1), withplot=TRUE, N = 200)
Modified: pkg/distrMod/R/qqplot.R
===================================================================
--- pkg/distrMod/R/qqplot.R 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/R/qqplot.R 2016-04-23 18:08:54 UTC (rev 1105)
@@ -6,7 +6,7 @@
## helper into distrMod
-.labelprep <- function(x,y,lab.pts,col.lbl,cex.lbl,which.lbs,which.Order,order.traf){
+.labelprep <- function(x,y,lab.pts,col.lbl,cex.lbl,adj.lbl,which.lbs,which.Order,order.traf){
n <- length(x)
rx <- rank(x)
xys <- cbind(x,y[rx])
@@ -26,7 +26,8 @@
col.lbl <- col.lbl[rx]
lab.pts <- lab.pts[rx]
cex.lbl <- cex.lbl[rx]
- return(list(x0=x0,y0=y0,lab=lab.pts[oN],col=col.lbl[oN],cex=cex.lbl[oN]))
+ adj.lbl <- adj.lbl[rx]
+ return(list(x0=x0,y0=y0,lab=lab.pts[oN],col=col.lbl[oN],cex=cex.lbl[oN],adj=adj.lbl[oN]))
}
@@ -79,7 +80,7 @@
col.pch = par("col"),## color for the plotted symbols
cex.lbl = par("cex"),## magnification factor for the plotted observation labels
col.lbl = par("col"),## color for the plotted observation labels
- adj.lbl = NULL, ## adj parameter for the plotted observation labels
+ adj.lbl = par("adj"),## adj parameter for the plotted observation labels
alpha.trsp = NA, ## alpha transparency to be added afterwards
jit.fac = 0, ## jittering factor used for discrete distributions
jit.tol = .Machine$double.eps, ## tolerance for jittering: if distance
@@ -134,6 +135,7 @@
function(x,a) x else function(x,a) mapply(x,alp.t,a1=a)
cex.pch <- .makeLenAndOrder(cex.pch,ord.x)
cex.lbl <- .makeLenAndOrder(cex.lbl,ord.x)
+ adj.lbl <- .makeLenAndOrder(adj.lbl,ord.x)
col.pch <- alp.f(.makeLenAndOrder(col.pch,ord.x),alp.v)
col.lbl <- alp.f(.makeLenAndOrder(col.lbl,ord.x),alp.v)
@@ -190,14 +192,14 @@
if(mfColRow) opar1 <- par(mfrow = c(1,1), no.readonly = TRUE)
ret <- do.call(stats::qqplot, args=mcl)
-
+ lbprep <- NULL
if(withLab&& plot.it){
lbprep <- .labelprep(xj,yc,lab.pts,
- col.lbl,cex.lbl,which.lbs,which.Order,order.traf)
+ col.lbl,cex.lbl, adj.lbl,which.lbs,which.Order,order.traf)
xlb0 <- if(datax) lbprep$x0 else lbprep$y0
ylb0 <- if(datax) lbprep$y0 else lbprep$x0
text(x = xlb0, y = ylb0, labels = lbprep$lab,
- cex = lbprep$cex, col = lbprep$col, adj = adj.lbl)
+ cex = lbprep$cex, col = lbprep$col, adj = lbprep$adj)
}
qqb <- NULL
@@ -232,6 +234,27 @@
}
}
+ qqplotInfo <- list(xy.0=xy, y.0=y, datax = datax,
+ withConf.pw=withConf.pw,
+ withConf.sim=withConf.sim,
+ alpha.CI=alpha.CI ,
+ col.pCI = col.pCI , lty.pCI = lty.pCI ,
+ lwd.pCI = lwd.pCI , pch.pCI = pch.pCI,
+ cex.pCI = cex.pCI ,
+ col.sCI = col.sCI , lty.sCI = lty.sCI ,
+ lwd.sCI = lwd.sCI , pch.sCI = pch.sCI,
+ cex.sCI = cex.sCI ,
+ n = n ,
+ exact.sCI = exact.sCI, exact.pCI = exact.pCI,
+ nosym.pCI = nosym.pCI, with.legend = with.legend,
+ legend.bg = legend.bg, legend.pos = legend.pos,
+ legend.cex = legend.cex, legend.pref = legend.pref,
+ legend.postf = legend.postf, legend.alpha = legend.alpha,
+ debug = debug,
+ args.stats.qqplot = mcl,
+ withLab = withLab,
+ lbprep = lbprep
+ )
if(plot.it){
qqb <- .confqq(xy, y, datax=datax, withConf.pw, withConf.sim, alpha.CI,
col.pCI, lty.pCI, lwd.pCI, pch.pCI, cex.pCI,
@@ -247,7 +270,9 @@
}
}
}
- return(invisible(c(ret,qqb)))
+ qqplotInfo <- c(ret, qqplotInfo, qqb)
+ class(qqplotInfo) <- c("qqplotInfo","DiagnInfo")
+ return(invisible(qqplotInfo))
})
## into distrMod
Modified: pkg/distrMod/man/0distrMod-package.Rd
===================================================================
--- pkg/distrMod/man/0distrMod-package.Rd 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/man/0distrMod-package.Rd 2016-04-23 18:08:54 UTC (rev 1105)
@@ -16,7 +16,7 @@
\tabular{ll}{
Package: \tab distrMod \cr
Version: \tab 2.6 \cr
-Date: \tab 2015-11-07 \cr
+Date: \tab 2016-04-23 \cr
Depends: \tab R(>= 2.14.0), distr(>= 2.5.2), distrEx(>= 2.4), RandVar(>= 0.6.3), MASS, stats4,
methods \cr
Imports: \tab startupmsg, sfsmisc, graphics, stats, grDevices \cr
@@ -24,7 +24,7 @@
ByteCompile: \tab yes \cr
License: \tab LGPL-3 \cr
URL: \tab http://distr.r-forge.r-project.org/\cr
-SVNRevision: \tab 1080 \cr
+SVNRevision: \tab 1104 \cr
}}
\section{Classes}{
Deleted: pkg/distrMod/man/internalmdeHelpers.Rd
===================================================================
--- pkg/distrMod/man/internalmdeHelpers.Rd 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/man/internalmdeHelpers.Rd 2016-04-23 18:08:54 UTC (rev 1105)
@@ -1,61 +0,0 @@
-\name{internal_mdehelpers_for_distrMod}
-\alias{internal_mdehelpers_for_distrMod}
-\alias{.CvMMDCovariance}
-
-\title{Internal helper functions for treating MDEstimators in package distrMod}
-
-\description{
-These functions are used internally by function \code{MDEstimator} in
-package ``distrMod''.}
-
-\usage{
-.CvMMDCovariance<- function(L2Fam, param, mu = distribution(L2Fam),
- withplot = FALSE, withpreIC = FALSE,
- N = getdistrOption("DefaultNrGridPoints")+1,
- rel.tol=.Machine$double.eps^0.3,
- TruncQuantile = getdistrOption("TruncQuantile"),
- IQR.fac = 15,
- ...)
-}
-
-
-\arguments{
- \item{L2Fam}{an object of class \code{L2ParamFamily};
- the parametric family at which to evaluate the MCE}
- \item{param}{an object of class \code{ParamFamParameter};
- contains the parameter value at which to evaluate the
- variance}
- \item{mu}{an object of class \code{UnivariateDistribution};
- the distribution on the reals at which to integrate the squared
- distance of the cdf's in the CvM-distance}
- \item{withplot}{logical; defaults to \code{FALSE}; if \code{TRUE} for diagnostic
- purposes plots the influence function of the CvM-MDE}
- \item{withpreIC}{logical; should corresponding IC of the CvM-MDE be returned?}
- \item{\dots}{currently not used}
- \item{N}{integer; the number of grid points at which to evaluate the antiderivative
- in case of an absolutely continuous distribution; more precisely, internally
- this becomes \eqn{2N+1}}
- \item{rel.tol}{numeric; relative tolerance; currently not used}
- \item{TruncQuantile}{numeric in (0,1); in case of an unbounded support of the
- distribution the quantile level at which to cut the distribution}
- \item{IQR.fac}{a positive numeric; a factor by which to multiply the IQR of the distribution
- to obtain a sensible cut of point for the integration bounds}
- }
-
-\details{
-\code{.CvMMDCovariance} computes the asymptotic covariance of the CvM-MDE according to
-H. Rieder (1994) "Robust Asymptotic Statistics".
- }
-
-\value{
-\item{.CvMMDCovariance}{if argument \code{withpreIC} is \code{TRUE}, then
-a list with elements the IC of the CvM-MDE and its covariance is returned, otherwise
-just the covariance}
-}
-
-\author{
- Peter Ruckdeschel \email{peter.ruckdeschel at uni-oldenburg.de}
-}
-
-\keyword{internal}
-\concept{utilities}
Modified: pkg/distrMod/man/internals.Rd
===================================================================
--- pkg/distrMod/man/internals.Rd 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/man/internals.Rd 2016-04-23 18:08:54 UTC (rev 1105)
@@ -18,7 +18,7 @@
.isUnitMatrix(m)
.csimpsum(fx)
.validTrafo(trafo, dimension, dimensionwithN)
-.CvMMDCovariance(L2Fam, param, mu = distribution(L2Fam),
+.CvMMDCovariance(L2Fam, param, mu = distribution(L2Fam),
withplot = FALSE, withpreIC = FALSE,
N = getdistrOption("DefaultNrGridPoints")+1,
rel.tol=.Machine$double.eps^0.3,
@@ -42,29 +42,30 @@
\item{trafo}{an object of class \code{MatrixorFunction}}
\item{dimension}{a numeric --- length of main part of the parameter}
\item{dimensionwithN}{a numeric --- length of main and nuisance part of the parameter}
+
\item{L2Fam}{an object of class \code{L2ParamFamily} --- for
which we want to determine the IC resp. the as. [co]variance of the corresponding
Minimum CvM estimator}
- \item{param}{an object of class \code{ParamFamParameter}, the parameter value
- at which we want to determine the IC resp. the as. [co]variance of the corresponding
- Minimum CvM estimator}
\item{mu}{an object of class \code{UnivariateDistribution}: integration
measure (resp. distribution) for CvM distance}
- \item{rel.tol}{relative tolerance for \code{distrExIntegrate}.}
- \item{TruncQuantile}{quantile for quantile based integration range.}
- \item{lowerTruncQuantile}{lower quantile for quantile based integration range.}
- \item{upperTruncQuantile}{upper quantile for quantile based integration range.}
- \item{IQR.fac}{factor for scale based integration range (i.e.;
- median of the distribution \eqn{\pm}{+-}\code{IQR.fac}\eqn{\times}{*}IQR).}
- \item{withplot}{logical: shall we plot corresponding ICs?}
+ \item{withplot}{logical; defaults to \code{FALSE}; if \code{TRUE} for diagnostic
+ purposes plots the influence function of the CvM-MDE}
\item{withpreIC}{logical: shall we return a list with components \code{preIC}
and \code{var} or just \code{var}; here \code{var} is the corresponding
asymptotic variance and \code{preIC} the corresponding
\code{EuclRandVarList} featuring as argument \code{Curve} in \code{IC}s of
package \pkg{RobAStBase}}
- \item{N}{a numeric: the number of gridpoints for constructing the
- \eqn{\mu}{mu}- resp. \eqn{P_\theta}{P_theta}-``primitive''
- function}
+ \item{\dots}{currently not used}
+ \item{N}{integer; the number of grid points at which to evaluate the antiderivative
+ in case of an absolutely continuous distribution; more precisely, internally
+ this becomes \eqn{2N+1}}
+ \item{rel.tol}{relative tolerance for \code{distrExIntegrate}.}
+ \item{TruncQuantile}{numeric in (0,1); in case of an unbounded support of the
+ distribution the quantile level at which to cut the distribution}
+ \item{IQR.fac}{a positive numeric; a factor by which to multiply the IQR of the distribution
+ to obtain a sensible cut of point for the integration bounds}
+ \item{lowerTruncQuantile}{lower quantile for quantile based integration range.}
+ \item{upperTruncQuantile}{upper quantile for quantile based integration range.}
\item{fx}{a vector of function evaluations multiplied by the gridwidth}
\item{distr}{an object of class \code{AbscontDistribution}}
\item{\dots}{further argument to be passed through --- so
@@ -87,9 +88,8 @@
\code{.validTrafo} checks whether the argument is a valid transformation.
-\code{.CvMMDCovariance} determines the IC resp. the as. [co]variance of
- the corresponding Minimum CvM estimator. Still some checking / optimization /
- improvement needed.
+\code{.CvMMDCovariance} computes the asymptotic covariance of the CvM-MDE
+according to H. Rieder (1994) "Robust Asymptotic Statistics".
\code{.show.with.sd} is code borrowed from \code{print.fitdistr} in
package \pkg{MASS} by B.D. Ripley. It pretty-prints estimates with corresponding
@@ -115,6 +115,9 @@
\code{preIC} and \code{var} ---see above}
\item{.show.with.sd}{\code{invisible()}}
\item{.deleteDim}{vector \code{x} without \code{dim} attribute}
+\item{.CvMMDCovariance}{if argument \code{withpreIC} is \code{TRUE}, then
+a list with elements the IC of the CvM-MDE and its covariance is returned, otherwise
+just the covariance}
}
\author{
Modified: pkg/distrMod/man/qqplot.Rd
===================================================================
--- pkg/distrMod/man/qqplot.Rd 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/man/qqplot.Rd 2016-04-23 18:08:54 UTC (rev 1105)
@@ -239,9 +239,9 @@
}
\examples{
set.seed(123)
-x <- rnorm(40,mean=15,sd=30)
-qqplot(x, Chisq(df=15))
-NF <- NormLocationScaleFamily(mean=15, sd=30)
+x <- rnorm(40,mean=5,sd=sqrt(10))
+qqplot(x, Chisq(df=5))
+NF <- NormLocationScaleFamily(mean=5, sd=30^.5)
qqplot(x, NF)
mlE <- MLEstimator(x, NF)
qqplot(x, mlE)
Modified: pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save
===================================================================
--- pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save 2016-04-23 17:09:34 UTC (rev 1104)
+++ pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save 2016-04-23 18:08:54 UTC (rev 1105)
@@ -1,3179 +1,3178 @@
-
-R version 3.2.2 Patched (2015-11-06 r69612) -- "Fire Safety"
-Copyright (C) 2015 The R Foundation for Statistical Computing
-Platform: x86_64-pc-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 <- "distrMod"
-> source(file.path(R.home("share"), "R", "examples-header.R"))
-> options(warn = 1)
-> library('distrMod')
-Loading required package: distr
-Loading required package: startupmsg
-:startupmsg> Utilities for Start-Up Messages (version 0.9.1)
-: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
-:SweaveListingUtils> 0.7)
-: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’
-
-The following objects are masked from ‘package:base’:
-
- library, require
-
-:distr> Object Oriented Implementation of Distributions (version
-:distr> 2.6)
-: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 objects are masked from ‘package:stats’:
-
- df, qqplot, sd
-
-Loading required package: distrEx
-:distrEx> Extensions of Package 'distr' (version 2.6)
-: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 objects are masked from ‘package:stats’:
-
- IQR, mad, median, var
-
-Loading required package: RandVar
-:RandVar> Implementation of random variables (version 0.9.2)
-: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 2.6)
-: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’
-
-The following object is masked from ‘package:stats4’:
-
- confint
-
-The following object is masked from ‘package:stats’:
-
- confint
-
-The following object is masked from ‘package:base’:
-
- norm
-
->
-> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
-> cleanEx()
-> nameEx("BetaFamily")
-> ### * BetaFamily
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: BetaFamily
-> ### Title: Generating function for Beta families
-> ### Aliases: BetaFamily
-> ### Keywords: models
->
-> ### ** Examples
->
-> (B1 <- BetaFamily())
-An object of class "BetaFamily"
-### name: Beta family
-
-### distribution: Distribution Object of Class: Beta
- shape1: 1
- shape2: 1
- ncp: 0
-
-### param: An object of class "ParamFamParameter"
-name: shape1 and shape2
-shape1: 1
-shape2: 1
-trafo:
- shape1 shape2
-shape1 1 0
-shape2 0 1
-
-### props:
-[1] "The Beta family is invariant in the following sense"
-[2] "if (x_i)~Beta(s1,s2) then (1-x_i)~Beta(s2,s1)"
-> FisherInfo(B1)
-An object of class "PosSemDefSymmMatrix"
- shape1 shape2
-shape1 1.0000000 -0.6449341
-shape2 -0.6449341 1.0000000
-> checkL2deriv(B1)
-precision of centering: 3.96327e-05 3.963591e-05
-precision of Fisher information:
- shape1 shape2
-shape1 -1.851068e-05 1.648326e-06
-shape2 1.648326e-06 -1.851068e-05
-precision of Fisher information - relativ error [%]:
- shape1 shape2
-shape1 -0.0018510679 -0.0002555806
-shape2 -0.0002555806 -0.0018510679
-condition of Fisher information:
-[1] 5.277691
-$maximum.deviation
-[1] 3.963591e-05
-
->
->
->
-> cleanEx()
-> nameEx("BiasType-class")
-> ### * BiasType-class
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: BiasType-class
-> ### Title: Bias Type
-> ### Aliases: BiasType-class name,BiasType-method name<-,BiasType-method
-> ### Keywords: classes
->
-> ### ** Examples
->
-> aB <- positiveBias()
-> name(aB)
-[1] "positive Bias"
->
->
->
-> cleanEx()
-> nameEx("BinomFamily")
-> ### * BinomFamily
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: BinomFamily
-> ### Title: Generating function for Binomial families
-> ### Aliases: BinomFamily
-> ### Keywords: models
->
-> ### ** Examples
->
-> (B1 <- BinomFamily(size = 25, prob = 0.25))
-An object of class "BinomFamily"
-### name: Binomial family
-
-### distribution: Distribution Object of Class: Binom
- size: 25
- prob: 0.25
-
-### param: An object of class "ParamFamParameter"
-name: probability of success
-prob: 0.25
-fixed part of param.:
- size: 25
-trafo:
- prob
-prob 1
-
-### props:
-[1] "The Binomial family is symmetric with respect to prob = 0.5;"
-[2] "i.e., d(Binom(size, prob))(k)=d(Binom(size,1-prob))(size-k)"
-> plot(B1)
-> FisherInfo(B1)
-An object of class "PosSemDefSymmMatrix"
- prob
-prob 133.3333
-> checkL2deriv(B1)
-precision of centering: -1.099042e-15
-precision of Fisher information:
- prob
-prob 2.842171e-14
-precision of Fisher information - relativ error [%]:
- prob
-prob 2.131628e-14
-condition of Fisher information:
-[1] 1
-$maximum.deviation
-[1] 2.842171e-14
-
->
->
->
-> cleanEx()
-> nameEx("CauchyLocationScaleFamily")
-> ### * CauchyLocationScaleFamily
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: CauchyLocationScaleFamily
-> ### Title: Generating function for Cauchy location and scale families
-> ### Aliases: CauchyLocationScaleFamily
-> ### Keywords: models
->
-> ### ** Examples
->
-> (C1 <- CauchyLocationScaleFamily())
-An object of class "CauchyLocationScaleFamily"
-### name: Cauchy Location and scale family
-
-### distribution: Distribution Object of Class: Cauchy
- location: 0
- scale: 1
-
-### param: An object of class "ParamWithScaleFamParameter"
-name: location and scale
-loc: 0
-scale: 1
-trafo:
- loc scale
-loc 1 0
-scale 0 1
-
-### props:
-[1] "The Cauchy Location and scale family is invariant under"
-[2] "the group of transformations 'g(x) = scale*x + loc'"
-[3] "with location parameter 'loc' and scale parameter 'scale'"
-> plot(C1)
-> FisherInfo(C1)
-An object of class "PosDefSymmMatrix"
- loc scale
-loc 0.5 0.0
-scale 0.0 0.5
-> ### need smaller integration range:
-> distrExoptions("ElowerTruncQuantile"=1e-4,"EupperTruncQuantile"=1e-4)
-> checkL2deriv(C1)
-precision of centering: 0 -0.02119711
-precision of Fisher information:
- loc scale
-loc -3.137524e-05 0.00000000
-scale 0.000000e+00 -0.02118143
-precision of Fisher information - relativ error [%]:
- loc scale
-loc -0.006275047 NaN
-scale NaN -4.236286
-condition of Fisher information:
-[1] 1
-$maximum.deviation
-[1] 0.02119711
-
-> distrExoptions("ElowerTruncQuantile"=1e-7,"EupperTruncQuantile"=1e-7)
->
->
->
-> cleanEx()
-> nameEx("Confint-class")
-> ### * Confint-class
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: Confint-class
-> ### Title: Confint-class
-> ### Aliases: Confint-class type,Confint-method call.estimate
-> ### call.estimate,Confint-method confint,Confint,missing-method
-> ### name.estimate name.estimate,Confint-method trafo.estimate
-> ### trafo.estimate,Confint-method samplesize.estimate
-> ### samplesize.estimate,Confint-method completecases.estimate
-> ### completecases.estimate,Confint-method nuisance.estimate
-> ### nuisance.estimate,Confint-method fixed.estimate
-> ### fixed.estimate,Confint-method show,Confint-method
-> ### print,Confint-method
-> ### Keywords: classes
->
-> ### ** Examples
->
-> ## some transformation
-> mtrafo <- function(x){
-+ nms0 <- c("scale","shape")
-+ nms <- c("shape","rate")
-+ fval0 <- c(x[2], 1/x[1])
-+ names(fval0) <- nms
-+ mat0 <- matrix( c(0, -1/x[1]^2, 1, 0), nrow = 2, ncol = 2,
-+ dimnames = list(nms,nms0))
-+ list(fval = fval0, mat = mat0)}
->
-> x <- rgamma(50, scale = 0.5, shape = 3)
->
-> ## parametric family of probability measures
-> G <- GammaFamily(scale = 1, shape = 2, trafo = mtrafo)
-> ## MLE
-> res <- MLEstimator(x = x, ParamFamily = G)
-> ci <- confint(res)
-> print(ci, digits = 4, show.details="maximal")
-A[n] asymptotic (CLT-based) confidence interval:
- 2.5 % 97.5 %
-shape 2.530 5.591
-rate 1.751 4.097
-Type of estimator: Maximum likelihood estimate
-samplesize: 50
-Call by which estimate was produced:
-MLEstimator(x = x, ParamFamily = G)
-Transformation of main parameter by which estimate was produced:
-function (x)
-{
- nms0 <- c("scale", "shape")
- nms <- c("shape", "rate")
- fval0 <- c(x[2], 1/x[1])
- names(fval0) <- nms
- mat0 <- matrix(c(0, -1/x[1]^2, 1, 0), nrow = 2, ncol = 2,
- dimnames = list(nms, nms0))
- list(fval = fval0, mat = mat0)
-}
-Trafo / derivative matrix at which estimate was produced:
- scale shape
-shape 0.000 1
-rate -8.549 0
-> print(ci, digits = 4, show.details="medium")
-A[n] asymptotic (CLT-based) confidence interval:
- 2.5 % 97.5 %
-shape 2.530 5.591
-rate 1.751 4.097
-Type of estimator: Maximum likelihood estimate
-samplesize: 50
-Call by which estimate was produced:
-MLEstimator(x = x, ParamFamily = G)
-> print(ci, digits = 4, show.details="minimal")
-A[n] asymptotic (CLT-based) confidence interval:
- 2.5 % 97.5 %
-shape 2.530 5.591
-rate 1.751 4.097
->
->
->
-> cleanEx()
-> nameEx("Estimate-class")
-> ### * Estimate-class
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: Estimate-class
-> ### Title: Estimate-class.
-> ### Aliases: Estimate-class name,Estimate-method name<-,Estimate-method
-> ### estimate estimate,Estimate-method estimate.call
-> ### estimate.call,Estimate-method Infos Infos,Estimate-method samplesize
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/distr -r 1105
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