[Distr-commits] r1180 - in pkg/distrMod: . R inst man tests/Examples vignettes
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sun Jul 8 16:23:41 CEST 2018
Author: ruckdeschel
Date: 2018-07-08 16:23:40 +0200 (Sun, 08 Jul 2018)
New Revision: 1180
Modified:
pkg/distrMod/DESCRIPTION
pkg/distrMod/NAMESPACE
pkg/distrMod/R/0distrModUtils.R
pkg/distrMod/R/L2GroupFamilies.R
pkg/distrMod/R/qqplot.R
pkg/distrMod/R/returnlevelplot.R
pkg/distrMod/inst/NEWS
pkg/distrMod/man/0distrMod-package.Rd
pkg/distrMod/man/MDEstimator.Rd
pkg/distrMod/man/internals-qqplot.Rd
pkg/distrMod/man/internals.Rd
pkg/distrMod/man/qqplot.Rd
pkg/distrMod/man/returnlevelplot.Rd
pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save
pkg/distrMod/vignettes/Estimate.pdf
pkg/distrMod/vignettes/ParamFamParameter.pdf
pkg/distrMod/vignettes/ProbFamily.pdf
pkg/distrMod/vignettes/distrMod.Rnw
pkg/distrMod/vignettes/distrMod.bib
Log:
[distrMod] merged branch 2.7 back to trunk
Modified: pkg/distrMod/DESCRIPTION
===================================================================
--- pkg/distrMod/DESCRIPTION 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/DESCRIPTION 2018-07-08 14:23:40 UTC (rev 1180)
@@ -1,6 +1,6 @@
Package: distrMod
-Version: 2.6.2
-Date: 2016-09-04
+Version: 2.7
+Date: 2015-11-07
Title: Object Oriented Implementation of Probability Models
Description: Implements S4 classes for probability models based on packages 'distr' and
'distrEx'.
@@ -10,11 +10,12 @@
Depends: R(>= 2.14.0), distr(>= 2.5.2), distrEx(>= 2.4), RandVar(>= 0.6.3), MASS, stats4,
methods
Imports: startupmsg, sfsmisc, graphics, stats, grDevices
-Suggests: ismev, evd, RobExtremes
+Suggests: ismev, evd,
+Enhances: RobExtremes
ByteCompile: yes
License: LGPL-3
Encoding: latin1
URL: http://distr.r-forge.r-project.org/
LastChangedDate: {$LastChangedDate$}
LastChangedRevision: {$LastChangedRevision$}
-SVNRevision: 1104
+SVNRevision: 1080
Modified: pkg/distrMod/NAMESPACE
===================================================================
--- pkg/distrMod/NAMESPACE 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/NAMESPACE 2018-07-08 14:23:40 UTC (rev 1180)
@@ -92,4 +92,4 @@
export("L2LocationUnknownScaleFamily", "L2ScaleUnknownLocationFamily")
export("meRes", "get.criterion.fct")
export("addAlphTrsp2col")
-export(".deleteDim",".isUnitMatrix", ".CvMMDCovariance")
+export(".deleteDim",".isUnitMatrix",".CvMMDCovariance")
Modified: pkg/distrMod/R/0distrModUtils.R
===================================================================
--- pkg/distrMod/R/0distrModUtils.R 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/R/0distrModUtils.R 2018-07-08 14:23:40 UTC (rev 1180)
@@ -16,8 +16,8 @@
lowerTruncQuantile = getdistrExOption("ElowerTruncQuantile"),
upperTruncQuantile = getdistrExOption("EupperTruncQuantile"),
IQR.fac = getdistrExOption("IQR.fac")){
- low0 <- q(distr)(lowerTruncQuantile)
- upp0 <- q(distr)(upperTruncQuantile,lower.tail=FALSE)
+ low0 <- q.l(distr)(lowerTruncQuantile)
+ upp0 <- q.l(distr)(upperTruncQuantile,lower.tail=FALSE)
me <- median(distr)
s1 <- IQR(distr)
low1 <- me - IQR.fac * s1
@@ -103,69 +103,58 @@
N1 <- 2*N+1
odd <- (1:N1)%%2==1
- ## 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:
- if(is(distr,"DiscreteDistribution")){
- x.seq0 <- x.seq <- support(distr)
- low <- min(x.seq)
- up <- max(x.seq)
- }else{
+ low0 <- q.l(distr)(TruncQuantile)
+ up0 <- q.l(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)
+
### 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,"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(missing(mu)) mu <- distr
+ low0.mu <- q.l(mu)(TruncQuantile)
+ up0.mu <- q.l(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)
- ## 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")){
+
+ if(is(distr,"DiscreteDistribution"))
+ x.seq <-support(distr)
+ else
+ {if(is(distr,"AbscontDistribution")){
+ x.seq0 <- seq(low, up, length = N1)
+ h0 <- diff(x.seq0[2:1])
+ x.seq <- x.seq0[odd]
+ }else{
+ x.seq <- seq(low,up, length = N)
+ }
+ }
+ if(is(mu,"DiscreteDistribution"))
x.mu.seq <- support(mu)
- 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")){
+ else
+ {if(is(mu,"AbscontDistribution")){
x.mu.seq0 <- seq(low.mu, up.mu, length = N1)
- h0.mu <- x.mu.seq0[1:2]%*%c(-1,1)
+ h0.mu <- diff(x.mu.seq0[2:1])
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))
@@ -188,35 +177,30 @@
d(distr)(x.seq0)
Delta0 <- h0*.csimpsum(Delta0x)
}else{
- 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)
+ 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 <- Delta1
-# print(Delta(x.seq))
+ else Delta <- function(x) Delta1(x)
+ # 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(x)^2 )
+ J <- E(object=distr, fun = function(x) Delta.0(x)^2 )
# print(J)
### CvM-IC phi
- phi <- function(x) Delta(x)/J
+ phi <- function(x) Delta.0(x)/J
## integrand phi x Ptheta in formula (51) [ibid]
phi1 <- function(x) phi(x) * p(distr)(x)
@@ -251,14 +235,13 @@
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(E1,E2,E4,E2-E4))
+# print(list(E2,E4,E2-E4))
}else{
@@ -396,7 +379,7 @@
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), withpreIC,withplot=TRUE, N = 200)
+N1 <- NormScaleFamily(); re=.CvMMDCovariance(N1,par=ParamFamParameter("",1), withICwithplot=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)
@@ -635,8 +618,8 @@
.NotInSupport <- function(x,D){
if(length(x)==0) return(logical(0))
- nInSupp <- which(x < q(D)(0))
- nInSupp <- unique(sort(c(nInSupp,which(x > q(D)(1)))))
+ nInSupp <- which(x < q.l(D)(0))
+ nInSupp <- unique(sort(c(nInSupp,which(x > q.l(D)(1)))))
nInSuppo <-
if("support" %in% names(getSlots(class(D))))
@@ -664,7 +647,7 @@
lx[.NotInSupport(x,D)] <- 4
- idx.0 <- ((x>q(D)(1)) | (x<q(D)(0)))
+ idx.0 <- ((x>q.l(D)(1)) | (x<q.l(D)(0)))
iG <- rep(FALSE,length(x))
if(is(D, "DiscreteDistribution")){
Modified: pkg/distrMod/R/L2GroupFamilies.R
===================================================================
--- pkg/distrMod/R/L2GroupFamilies.R 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/R/L2GroupFamilies.R 2018-07-08 14:23:40 UTC (rev 1180)
@@ -333,7 +333,7 @@
}
mad.const <- 1/ if (is(distrSymm, "NoSymmetry"))
- mad(centraldistribution) else q(centraldistribution)(.75)
+ mad(centraldistribution) else q.l(centraldistribution)(.75)
param0 <- c(loc, scale)
names(param0) <- locscalename
Modified: pkg/distrMod/R/qqplot.R
===================================================================
--- pkg/distrMod/R/qqplot.R 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/R/qqplot.R 2018-07-08 14:23:40 UTC (rev 1180)
@@ -122,7 +122,7 @@
ord.x <- order(xj)
pp <- ppoints(n)
- yc <- q(y)(pp)
+ yc <- q.l(y)(pp)
yc.o <- yc
@@ -146,9 +146,9 @@
if(check.NotInSupport){
xo <- x[ord.x]
- nInSupp <- which(xo < q(y)(0))
+ nInSupp <- which(xo < q.l(y)(0))
- nInSupp <- unique(sort(c(nInSupp,which( xo > q(y)(1)))))
+ nInSupp <- unique(sort(c(nInSupp,which( xo > q.l(y)(1)))))
if("support" %in% names(getSlots(class(y))))
nInSupp <- unique(sort(c(nInSupp,which( ! xo %in% support(y)))))
if("gaps" %in% names(getSlots(class(y))))
@@ -270,7 +270,7 @@
}
}
}
- qqplotInfo <- c(ret, qqplotInfo, qqb)
+ qqplotInfo <- c(call=mc, ret, qqplotInfo, qqb)
class(qqplotInfo) <- c("qqplotInfo","DiagnInfo")
return(invisible(qqplotInfo))
})
@@ -292,8 +292,10 @@
if(!is(yD,"UnivariateDistribution"))
stop("Not yet implemented.")
- return(invisible(do.call(getMethod("qqplot", signature(x="ANY", y="UnivariateDistribution")),
- args=mcl)))
+ retv <- do.call(getMethod("qqplot", signature(x="ANY", y="UnivariateDistribution")),
+ args=mcl)
+ retv$call <- mc
+ return(invisible(retv))
})
setMethod("qqplot", signature(x = "ANY",
@@ -321,7 +323,9 @@
PFam0 <- modifyModel(PFam, param)
mcl$y <- PFam0
- return(invisible(do.call(getMethod("qqplot", signature(x="ANY", y="ProbFamily")),
- args=mcl)))
+ retv <- do.call(getMethod("qqplot", signature(x="ANY", y="ProbFamily")),
+ args=mcl)
+ retv$call <- mc
+ return(invisible(retv))
})
Modified: pkg/distrMod/R/returnlevelplot.R
===================================================================
--- pkg/distrMod/R/returnlevelplot.R 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/R/returnlevelplot.R 2018-07-08 14:23:40 UTC (rev 1180)
@@ -54,7 +54,7 @@
col.pch = par("col"),## color for the plotted symbols
cex.lbl = par("cex"),## magnification factor for the plotted observation labels
col.lbl = par("col"),## color for the plotted observation labels
- adj.lbl = NULL, ## adj parameter for the plotted observation labels
+ adj.lbl = par("adj"),## adj parameter for the plotted observation labels
alpha.trsp = NA, ## alpha transparency to be added afterwards
jit.fac = 0, ## jittering factor used for discrete distributions
jit.tol = .Machine$double.eps, ## tolerance for jittering: if distance
@@ -120,13 +120,13 @@
}
pp <- ppoints(length(xj))
- yc.o <- q(y)(pp)
+ yc.o <- q.l(y)(pp)
ycl <- p2rl(yc.o)
### extend range somewhat
# pyn <- p(y)(10^(seq(-1, 3.75 + log10(npy), by = 0.1)))
xyall <- force(sort(unique(c(yc.o,x,
- q(y)(c(seq(0.01, 0.09, by = 0.01),(1:9)/10,
+ q.l(y)(c(seq(0.01, 0.09, by = 0.01),(1:9)/10,
0.95, 0.99, 0.995, 0.999))
))))
rxyall <- (max(xyall)-min(xyall))*0.6
@@ -162,9 +162,9 @@
if(check.NotInSupport){
xo <- x[ord.x]
- nInSupp <- which(xo < q(y)(0))
+ nInSupp <- which(xo < q.l(y)(0))
- nInSupp <- unique(sort(c(nInSupp,which( xo > q(y)(1)))))
+ nInSupp <- unique(sort(c(nInSupp,which( xo > q.l(y)(1)))))
if("support" %in% names(getSlots(class(y))))
nInSupp <- unique(sort(c(nInSupp,which( ! xo %in% support(y)))))
if("gaps" %in% names(getSlots(class(y))))
Modified: pkg/distrMod/inst/NEWS
===================================================================
--- pkg/distrMod/inst/NEWS 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/inst/NEWS 2018-07-08 14:23:40 UTC (rev 1180)
@@ -8,6 +8,20 @@
information)
##############
+v 2.7
+##############
+
+user-visible CHANGES:
++ replaced http://CRAN... by https://CRAN... (also in CITATION and similar files)
++ exported .CvMMDCovariance in distrMod
++ added call to return value of qqplot
+
+under the hood:
++ wherever possible also use q.l internally instead of q to
+ provide functionality in IRKernel
++ fixed omegahat.net issue (raised by K.Hornik,(24.10.2016, 18:08)
+
+##############
v 2.6
##############
@@ -64,7 +78,6 @@
BUGFIXES:
-+ fixed an issue with MDEstimator and validParameter
+ fixed issue with slot withPosRestr in ParamFamParameter.R
+ fixed issue with check.validity (reported by B.Spangl)
+ fixed some minor issue in existsPIC (in case we get 0 matrix, and less strict tolerance)
Modified: pkg/distrMod/man/0distrMod-package.Rd
===================================================================
--- pkg/distrMod/man/0distrMod-package.Rd 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/man/0distrMod-package.Rd 2018-07-08 14:23:40 UTC (rev 1180)
@@ -15,16 +15,17 @@
\details{
\tabular{ll}{
Package: \tab distrMod \cr
-Version: \tab 2.6 \cr
-Date: \tab 2016-04-23 \cr
+Version: \tab 2.7 \cr
+Date: \tab 2015-11-07 \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
-Suggests: \tab ismev, evd, RobExtremes \cr
+Suggests: \tab ismev, evd\cr
+Enhances: RobExtremes\cr
ByteCompile: \tab yes \cr
License: \tab LGPL-3 \cr
URL: \tab http://distr.r-forge.r-project.org/\cr
-SVNRevision: \tab 1104 \cr
+SVNRevision: \tab 1080 \cr
}}
\section{Classes}{
@@ -291,7 +292,7 @@
M. Kohl and P. Ruckdeschel (2010):
R Package distrMod: S4 Classes and Methods for Probability Models.
Journal of Statistical Software, 35(10), 1-27.
-\url{http://www.jstatsoft.org/v35/i10/}
+\url{https://www.jstatsoft.org/v35/i10/}
(see also \code{vignette("distrMod")})
Modified: pkg/distrMod/man/MDEstimator.Rd
===================================================================
--- pkg/distrMod/man/MDEstimator.Rd 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/man/MDEstimator.Rd 2018-07-08 14:23:40 UTC (rev 1180)
@@ -74,7 +74,7 @@
%\note{}
\seealso{\code{\link{ParamFamily-class}}, \code{\link{ParamFamily}},
\code{\link{MCEstimator}}, \code{\link{MCEstimate-class}},
- \code{\link[MASS]{fitdistr}}, \code{\link{.CvMMDCovariance}}}
+ \code{\link[MASS]{fitdistr}} }
\examples{
## (empirical) Data
x <- rgamma(50, scale = 0.5, shape = 3)
@@ -90,7 +90,9 @@
## von Mises minimum distance estimator with default mu
MDEstimator(x = x, ParamFamily = G, distance = CvMDist,
- asvar.fct = .CvMMDCovariance)
+ asvar.fct = distrMod:::.CvMMDCovariance)
+#*** variance routine is still in testing phase so not yet
+#*** exported to namespace
## von Mises minimum distance estimator with mu = N(0,1)
MDEstimator(x = x, ParamFamily = G, distance = CvMDist, mu = Norm())
Modified: pkg/distrMod/man/internals-qqplot.Rd
===================================================================
--- pkg/distrMod/man/internals-qqplot.Rd 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/man/internals-qqplot.Rd 2018-07-08 14:23:40 UTC (rev 1180)
@@ -18,7 +18,7 @@
\item{y}{a (numeric) vector of same length as \code{x}}
\item{cex.lbl}{magnification factor for the plotted observation labels}
\item{col.lbl}{color for the plotted observation labels}
-\item{adj.lbl}{adj parameter for the plotted observation labels}
+\item{adj.lbl}{adjustment factor for the plotted observation labels}
\item{lab.pts}{character or \code{NULL}; observation labels to be used}
\item{which.lbs}{integer or \code{NULL}; which observations shall be labelled}
\item{which.Order}{integer or \code{NULL}; which of the ordered (remaining) observations shall be labelled}
@@ -45,7 +45,6 @@
\code{lab} (the thinned out and ordered vector of labels \code{lab.pts}),
\code{col} (the thinned out and ordered vector of colors \code{col.lbs}),
\code{cex} (the thinned out and ordered vector of magnification factors \code{cex.lbs}).
-\code{adj} (the thinned out and ordered vector of adjacencies \code{adj.lbs}).
}
}
Modified: pkg/distrMod/man/internals.Rd
===================================================================
--- pkg/distrMod/man/internals.Rd 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/man/internals.Rd 2018-07-08 14:23:40 UTC (rev 1180)
@@ -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,
@@ -42,30 +42,29 @@
\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{withplot}{logical; defaults to \code{FALSE}; if \code{TRUE} for diagnostic
- purposes plots the influence function of the CvM-MDE}
+ \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{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{\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{N}{a numeric: the number of gridpoints for constructing the
+ \eqn{\mu}{mu}- resp. \eqn{P_\theta}{P_theta}-``primitive''
+ function}
\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
@@ -88,8 +87,9 @@
\code{.validTrafo} checks whether the argument is a valid transformation.
-\code{.CvMMDCovariance} computes the asymptotic covariance of the CvM-MDE
-according to H. Rieder (1994) "Robust Asymptotic Statistics".
+\code{.CvMMDCovariance} determines the IC resp. the as. [co]variance of
+ the corresponding Minimum CvM estimator. Still some checking / optimization /
+ improvement needed.
\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
@@ -115,9 +115,6 @@
\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 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/man/qqplot.Rd 2018-07-08 14:23:40 UTC (rev 1180)
@@ -144,54 +144,12 @@
}
}
\value{
- A list of elements containing the information needed to compute the
- respective QQ plot, in particular it extends the elements of the
- return value of function \code{\link[stats:qqnorm]{qqplot}}
- from package \pkg{stats}, i.e., a
- list with components \code{x} and \code{y} for x and y coordinates
- of the plotted points; this list is of S3 class
- \code{c("qqplotInfo","DiagnInfo")}, and more specifically it contains
+ As for function \code{\link[stats:qqnorm]{qqplot}} from package \pkg{stats}: a
+ list with components
\item{x}{The x coordinates of the points that were/would be plotted}
\item{y}{The corresponding quantiles of the second distribution,
\emph{including \code{\link{NA}}s}.}
-
- \item{xy.0}{xy}
- \item{y.0}{y}
- \item{datax}{argument \code{datax} from the call.}
- \item{withConf.pw}{argument \code{withConf.pw} from the call.}
- \item{withConf.sim}{argument \code{withConf.sim} from the call.}
- \item{alpha.CI}{argument \code{alpha.CI } from the call.}
- \item{col.pCI}{argument \code{col.pCI} from the call.}
- \item{lty.pCI}{argument \code{lty.pCI} from the call.}
- \item{lwd.pCI}{argument \code{lwd.pCI} from the call.}
- \item{pch.pCI}{argument \code{pch.pCI} from the call.}
- \item{cex.pCI}{argument \code{cex.pCI} from the call.}
- \item{col.sCI}{argument \code{col.sCI} from the call.}
- \item{lty.sCI}{argument \code{lty.sCI} from the call.}
- \item{lwd.sCI}{argument \code{lwd.sCI} from the call.}
- \item{pch.sCI}{argument \code{pch.sCI} from the call.}
- \item{cex.sCI}{argument \code{cex.sCI} from the call.}
- \item{n}{argument \code{n} from the call.}
- \item{exact.sCI}{argument \code{exact.sCI} from the call.}
- \item{exact.pCI}{argument \code{exact.pCI} from the call.}
- \item{nosym.pCI}{argument \code{nosym.pCI} from the call.}
- \item{with.legend}{argument \code{with.legend} from the call.}
- \item{legend.bg}{argument \code{legend.bg} from the call.}
- \item{legend.pos}{argument \code{legend.pos} from the call.}
- \item{legend.cex}{argument \code{legend.cex} from the call.}
- \item{legend.pref}{argument \code{legend.pref} from the call.}
- \item{legend.postf}{argument \code{legend.postf} from the call.}
- \item{legend.alpha}{argument \code{legend.alpha} from the call.}
- \item{debug}{argument \code{debug} from the call.}
- \item{args.stats.qqplot}{the arguments of the call to \code{mcl} from the call.}
- \item{withLab}{argument \code{withLab} from the call to
- \code{stats::qqplot} from within this QQ plot method.}
- \item{lbprep}{the return value of the label preparation from within
- this function, i.e., a list with elements
- \code{x0}, \code{y0}, \code{lab}, \code{col}, \code{cex},
- \code{adj}.}
-
- \item{crit}{A matrix with the lower and upper confidence bounds
+ \item{crit}{A matrix with the lower and upper confidence bounds
(computed by \code{qqbounds}).}
\item{err}{logical vector of length 2.}
(elements \code{crit} and \code{err} are taken from the return
@@ -239,9 +197,9 @@
}
\examples{
set.seed(123)
-x <- rnorm(40,mean=5,sd=sqrt(10))
-qqplot(x, Chisq(df=5))
-NF <- NormLocationScaleFamily(mean=5, sd=30^.5)
+x <- rnorm(40,mean=15,sd=30)
+qqplot(x, Chisq(df=15))
+NF <- NormLocationScaleFamily(mean=15, sd=30)
qqplot(x, NF)
mlE <- MLEstimator(x, NF)
qqplot(x, mlE)
Modified: pkg/distrMod/man/returnlevelplot.Rd
===================================================================
--- pkg/distrMod/man/returnlevelplot.Rd 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/man/returnlevelplot.Rd 2018-07-08 14:23:40 UTC (rev 1180)
@@ -21,7 +21,7 @@
col.sCI = "tomato2", lty.sCI = 4, lwd.sCI = 2, pch.sCI = par("pch"),
cex.sCI = par("cex"), added.points.CI = TRUE,
cex.pch = par("cex"), col.pch = par("col"),
- cex.lbl = par("cex"), col.lbl = par("col"), adj.lbl = NULL,
+ cex.lbl = par("cex"), col.lbl = par("col"), adj.lbl = par("adj"),
alpha.trsp = NA, jit.fac = 0, jit.tol = .Machine$double.eps,
check.NotInSupport = TRUE, col.NotInSupport = "red",
with.legend = TRUE, legend.bg = "white",
Modified: pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save
===================================================================
--- pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save 2018-07-08 14:23:04 UTC (rev 1179)
+++ pkg/distrMod/tests/Examples/distrMod-Ex.Rout.save 2018-07-08 14:23:40 UTC (rev 1180)
@@ -1,7 +1,7 @@
-R Under development (unstable) (2016-08-31 r71184) -- "Unsuffered Consequences"
-Copyright (C) 2016 The R Foundation for Statistical Computing
-Platform: i386-w64-mingw32/i386 (32-bit)
+R Under development (unstable) (2015-05-02 r68310) -- "Unsuffered Consequences"
+Copyright (C) 2015 The R Foundation for Statistical Computing
+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.
@@ -20,23 +20,10 @@
> pkgname <- "distrMod"
> source(file.path(R.home("share"), "R", "examples-header.R"))
> options(warn = 1)
-> options(pager = "console")
-> base::assign(".ExTimings", "distrMod-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]
-+ options(OutDec = '.')
-+ format(x[1L:3L], digits = 7L)
-+ },
-+ pos = 'CheckExEnv')
->
-> ### * </HEADER>
> library('distrMod')
Loading required package: distr
Loading required package: startupmsg
-:startupmsg> Utilities for Start-Up Messages (version 0.9.3)
+:startupmsg> Utilities for Start-Up Messages (version 0.9.1)
:startupmsg>
:startupmsg> For more information see ?"startupmsg",
:startupmsg> NEWS("startupmsg")
@@ -45,7 +32,7 @@
Loading required package: SweaveListingUtils
:SweaveListingUtils> Utilities for Sweave Together with
:SweaveListingUtils> TeX 'listings' Package (version
-:SweaveListingUtils> 0.7.5)
+:SweaveListingUtils> 0.7)
:SweaveListingUtils>
:SweaveListingUtils> NOTE: Support for this package
:SweaveListingUtils> will stop soon.
@@ -71,9 +58,9 @@
:SweaveListingUtils> vignette("ExampleSweaveListingUtils").
-Attaching package: 'SweaveListingUtils'
+Attaching package: ‘SweaveListingUtils’
-The following objects are masked from 'package:base':
+The following objects are masked from ‘package:base’:
library, require
@@ -97,9 +84,9 @@
:distr> vignette("distr").
-Attaching package: 'distr'
+Attaching package: ‘distr’
-The following objects are masked from 'package:stats':
+The following objects are masked from ‘package:stats’:
df, qqplot, sd
@@ -121,14 +108,14 @@
:distrEx> vignette("distr").
-Attaching package: 'distrEx'
+Attaching package: ‘distrEx’
-The following objects are masked from 'package:stats':
+The following objects are masked from ‘package:stats’:
IQR, mad, median, var
Loading required package: RandVar
-:RandVar> Implementation of Random Variables (version 1.0)
+:RandVar> Implementation of random variables (version 0.9.2)
:RandVar>
:RandVar> For more information see ?"RandVar", NEWS("RandVar"), as
:RandVar> well as
@@ -139,7 +126,7 @@
Loading required package: MASS
Loading required package: stats4
:distrMod> Object Oriented Implementation of Probability Models
-:distrMod> (version 2.6.1)
+:distrMod> (version 2.6)
:distrMod>
:distrMod> Some functions from pkg's 'base' and 'stats' are
:distrMod> intentionally masked ---see distrModMASK().
@@ -158,17 +145,17 @@
:distrMod> vignette("distr").
-Attaching package: 'distrMod'
+Attaching package: ‘distrMod’
-The following object is masked from 'package:stats4':
+The following object is masked from ‘package:stats4’:
confint
-The following object is masked from 'package:stats':
+The following object is masked from ‘package:stats’:
confint
-The following object is masked from 'package:base':
+The following object is masked from ‘package:base’:
norm
@@ -180,7 +167,6 @@
>
> flush(stderr()); flush(stdout())
>
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: BetaFamily
> ### Title: Generating function for Beta families
> ### Aliases: BetaFamily
@@ -215,7 +201,7 @@
shape1 1.0000000 -0.6449341
shape2 -0.6449341 1.0000000
> checkL2deriv(B1)
-precision of centering: 3.963281e-05 3.963334e-05
+precision of centering: 3.96327e-05 3.963591e-05
precision of Fisher information:
shape1 shape2
shape1 -1.851068e-05 1.648326e-06
@@ -227,20 +213,17 @@
condition of Fisher information:
[1] 5.277691
$maximum.deviation
-[1] 3.963334e-05
+[1] 3.963591e-05
>
>
>
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("BetaFamily", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
> cleanEx()
> nameEx("BiasType-class")
> ### * BiasType-class
>
> flush(stderr()); flush(stdout())
>
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: BiasType-class
> ### Title: Bias Type
> ### Aliases: BiasType-class name,BiasType-method name<-,BiasType-method
@@ -254,15 +237,12 @@
>
>
>
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("BiasType-class", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
> cleanEx()
> nameEx("BinomFamily")
> ### * BinomFamily
>
> flush(stderr()); flush(stdout())
>
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: BinomFamily
> ### Title: Generating function for Binomial families
> ### Aliases: BinomFamily
@@ -296,13 +276,13 @@
prob
prob 133.3333
> checkL2deriv(B1)
-precision of centering: -2.855253e-15
+precision of centering: -1.099042e-15
precision of Fisher information:
- prob
-prob -2.842171e-14
+ prob
+prob 2.842171e-14
precision of Fisher information - relativ error [%]:
- prob
-prob -2.131628e-14
+ prob
+prob 2.131628e-14
condition of Fisher information:
[1] 1
$maximum.deviation
@@ -311,15 +291,12 @@
>
>
>
-> base::assign(".dptime", (proc.time() - get(".ptime", pos = "CheckExEnv")), pos = "CheckExEnv")
-> base::cat("BinomFamily", base::get(".format_ptime", pos = 'CheckExEnv')(get(".dptime", pos = "CheckExEnv")), "\n", file=base::get(".ExTimings", pos = 'CheckExEnv'), append=TRUE, sep="\t")
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/distr -r 1180
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