[Robast-commits] r108 - branches/robast-0.6/pkg/RandVar/inst/doc
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Jul 21 14:01:18 CEST 2008
Author: stamats
Date: 2008-07-21 14:01:18 +0200 (Mon, 21 Jul 2008)
New Revision: 108
Removed:
branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.aux
branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.brf
branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.log
branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.out
branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.tex
branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.toc
Log:
log-files removed
Deleted: branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.aux
===================================================================
--- branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.aux 2008-07-21 12:00:24 UTC (rev 107)
+++ branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.aux 2008-07-21 12:01:18 UTC (rev 108)
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Deleted: branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.brf
===================================================================
--- branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.brf 2008-07-21 12:00:24 UTC (rev 107)
+++ branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.brf 2008-07-21 12:01:18 UTC (rev 108)
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Deleted: branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.log
===================================================================
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--- branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.out 2008-07-21 12:00:24 UTC (rev 107)
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@@ -1,3 +0,0 @@
-\BOOKMARK [1][-]{section.1}{S4 Classes}{}
-\BOOKMARK [1][-]{section.2}{Functions and Methods}{}
-\BOOKMARK [1][-]{section.3}{Odds and Ends}{}
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--- branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.tex 2008-07-21 12:00:24 UTC (rev 107)
+++ branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.tex 2008-07-21 12:01:18 UTC (rev 108)
@@ -1,466 +0,0 @@
-%\VignetteIndexEntry{RandVar}
-%\VignetteDepends{distr,distrEx}
-%\VignetteKeywords{random variable, S4 classes, S4 methods}
-%\VignettePackage{RandVar}
-%
-\documentclass[11pt]{article}
-\usepackage{geometry}\usepackage{color}
-\usepackage{ifpdf}
-\definecolor{darkblue}{rgb}{0.0,0.0,0.75}
-\usepackage[%
-baseurl={http://www.stamats.de},%
-pdftitle={RandVar: Implementation of random variables by means of S4 classes and methods},%
-pdfauthor={Matthias Kohl},%
-pdfsubject={RandVar},%
-pdfkeywords={random variable, S4 classes, S4 methods},%
-pagebackref,bookmarks,colorlinks,linkcolor=darkblue,citecolor=darkblue,%
-pagecolor=darkblue,raiselinks,plainpages,pdftex]{hyperref}
-%
-\markboth{\sl Packages ``{\tt RandVar}''}{\sl Packages ``{\tt RandVar}''}
-%
-% -------------------------------------------------------------------------------
-\newcommand{\code}[1]{{\tt #1}}
-\newcommand{\pkg}[1]{{\tt "#1"}}
-\newcommand{\pkgversion}{{\tt 2.0}}
-\newcommand{\pkgExversion}{{\tt 0.6.2}}
-% -------------------------------------------------------------------------------
-%
-% -------------------------------------------------------------------------------
-\usepackage{/home/btm722/RTOP/R-2-7-branch/share/texmf/Sweave}
-\begin{document}
-% -------------------------------------------------------------------------------
-\title{RandVar: Implementation of random variables by means
- of {\tt S4} classes and methods}
-\author{Matthias Kohl\\
-e-Mail: {\tt matthias.kohl at stamats.de}\\
-}
-\maketitle
-% -------------------------------------------------------------------------------
-\begin{abstract}
-% -------------------------------------------------------------------------------
-In this package we implement random variables by means of {\tt S4} classes
-and methods. This vignette corresponds to Appendix D.2 in Kohl~(2005)~\cite{MK:05}.
-% -------------------------------------------------------------------------------
-\end{abstract}
-% -------------------------------------------------------------------------------
-\tableofcontents
-% -------------------------------------------------------------------------------
-\clearpage
-% -----------------------------------------------------------------------
-\section{{\tt S4} Classes}
-% -----------------------------------------------------------------------
-The {\tt S4} class {\tt RandVariable} (cf.\ Figure~\ref{ap.Rpack.RandVar.dia1})
-has the slots {\tt Map}, {\tt Domain} and {\tt Range} where {\tt Map}
-contains a list of functions which are measurable maps from {\tt Domain}
-to {\tt Range}. The elements contained in the list {\tt Map} must be functions in
-one argument named {\tt x}. We do not allow further parameters for these
-functions as this would lead to inconsistent objects. Strictly speaking, an object of
-class {\tt RandVariable} would represent not only one random variable but a whole
-set of random variables depending on these parameters.
-% -----------------------------------------------------------------------
-\par
-The slots {\tt Domain} and {\tt Range} are filled with an object of
-class {\tt OptionalrSpace}; i.e., they contain {\tt NULL} or an object of class
-{\tt rSpace} (see package {\tt distr}~\cite{distr}). In case of
-{\tt EuclRandVariable} and {\tt RealRandVariable} the slot {\tt Range} is filled
-with an object of class {\tt Euclideanspace} and {\tt Reals}, respectively. The
-class {\tt EuclRandMatrix} additionally has the slot {\tt Dim} which is a vector
-of integers and contains the dimensions of the Euclidean random matrix.
-% -----------------------------------------------------------------------
-\par
-Using these {\tt S4} classes there are two possibilities to implement a ${\rm R}^k$
-valued random variable. First, we could define a {\tt EuclRandVariable}
-whose slot {\tt Map} contains a list with one function which maps to ${\rm R}^k$;
-i.e., the slot {\tt Range} is a $k$-dimensional Euclidean space. Second, we could
-define a {\tt EuclRandVariable} whose slot {\tt Map} contains a list with $n$
-functions (projections) which map to ${\rm R}^m$ where $k = m*n$. Now, the slot
-{\tt Range} is an $m$-dimensional Euclidean space.
-Since it is sometimes convenient to regard a ${\rm R}^k$ valued random variable
-as measurable map consisting of ${\rm R}^{k_i}$ valued maps where $\sum k_i = k$,
-we introduce a further class called {\tt EuclRandVarList}.
-With this class we can now define ${\rm R}^k$ valued random variables as a list
-of ${\rm R}^{k_i}$ valued random variables with compatible domains. More precisely,
-the elements of a {\tt EuclRandVarList} may even have very different ranges
-(not necessarily Euclidean spaces) they only need to have compatible
-domains which is checked via the generic function {\tt compatibleDomains}.
-% -----------------------------------------------------------------------
-\begin{figure}[!ht]
-\begin{center}
- \ifpdf
- \includegraphics[scale=1.0, viewport = 14 15 244 275]{RandVariable.pdf}
- \else
- \includegraphics[scale=1.0]{RandVariable.eps}
- \fi
- \caption[Class {\tt RandVariable} and Subclasses]{Class
- {\tt RandVariable} and subclasses.}
- \label{ap.Rpack.RandVar.dia1}
-\end{center}
-\end{figure}
-% -----------------------------------------------------------------------
-\newpage
-\section{Functions and Methods}
-% -----------------------------------------------------------------------
-As in case of package {\tt distrEx}~\cite{distr}, we follow the advices of
-Section~7.3 of \cite{Cham:98} and \cite{Gent:03}. That is, we introduce
-generating functions as well as accessor and replacement functions. A short
-description of the implemented generating functions is given in
-Table~\ref{ap.Rpack.RandVar.tab.gen}.
-% -----------------------------------------------------------------------
-\begin{table}[!ht]
-\begin{center}
-\begin{tabular}{p{4cm}|p{7.5cm}}
- \textbf{Generating Function} & \textbf{Description} \\ \hline\hline
- {\tt EuclRandMatrix} & Generates an object of class {\tt EuclRandMatrix}\\ \hline
- {\tt EuclRandVariable} & Generates an object of class {\tt EuclRandVariable}\\ \hline
- {\tt EuclRandVarList} & Generates an object of class {\tt EuclRandVarList}\\ \hline
- {\tt RandVariable} & Generates an object of class {\tt RandVariable}\\ \hline
- {\tt RealRandVariable} & Generates an object of class {\tt RealRandVariable}
-\end{tabular}
-\caption[Generating Functions of Package {\tt RandVar}]{Generating
-functions of package {\tt RandVar}.}\label{ap.Rpack.RandVar.tab.gen}%
-\end{center}
-\end{table}
-% -----------------------------------------------------------------------
-\par\noindent
-While there are accessor functions for all slots of the newly defined
-{\tt S4} classes, replacement functions are only implemented for those
-slots a user should modify.
-% -----------------------------------------------------------------------
-\par
-Our next goal was that one can use these classes of random variables like
-ordinary numeric vectors or matrices. Hence, we overloaded the {\tt S4}
-group generic functions {\tt Arith} and {\tt Math} as well as matrix
-multiplication {\tt \%*\%}. For the matrix multiplication of {\tt EuclRandVarList}s
-we additionally introduced the operator {\tt \%m\%}.
-Now, if we have random variables {\tt X} and {\tt Y}, a numerical
-vector {\tt v} and a numerical matrix {\tt M} (with compatible dimensions)
-we can for instance generate
-\begin{Schunk}
-\begin{Sinput}
-> library(RandVar)
-> (X <- RealRandVariable(Map = list(function(x) {
-+ x
-+ }, function(x) {
-+ x^2
-+ }), Domain = Reals(), Range = Reals()))
-\end{Sinput}
-\begin{Soutput}
-An object of class “RealRandVariable”
-length of Map: 2
-Domain: Real Space with dimension 1
-Range: Real Space with dimension 1
-\end{Soutput}
-\begin{Sinput}
-> Map(X)
-\end{Sinput}
-\begin{Soutput}
-[[1]]
-function (x)
-{
- x
-}
-
-[[2]]
-function (x)
-{
- x^2
-}
-\end{Soutput}
-\begin{Sinput}
-> evalRandVar(X, 2)
-\end{Sinput}
-\begin{Soutput}
- [,1]
-[1,] 2
-[2,] 4
-\end{Soutput}
-\begin{Sinput}
-> evalRandVar(X, as.matrix(seq(2, 10, 2)))
-\end{Sinput}
-\begin{Soutput}
-, , 1
-
- [,1] [,2] [,3] [,4] [,5]
-[1,] 2 4 6 8 10
-[2,] 4 16 36 64 100
-\end{Soutput}
-\begin{Sinput}
-> R1 <- exp(X - 1)
-> Map(R1)
-\end{Sinput}
-\begin{Soutput}
-[[1]]
-function (x)
-{
- f1 <- function (x)
- {
- f1 <- function (x)
- {
- x
- }
- f1(x) - 1
- }
- exp(f1(x))
-}
-<environment: 0x8cd175c>
-
-[[2]]
-function (x)
-{
- f1 <- function (x)
- {
- f1 <- function (x)
- {
- x^2
- }
- f1(x) - 1
- }
- exp(f1(x))
-}
-<environment: 0x8cd175c>
-\end{Soutput}
-\begin{Sinput}
-> R2 <- exp(X - 1:2)
-> Map(R2)
-\end{Sinput}
-\begin{Soutput}
-[[1]]
-function (x)
-{
- f1 <- function (x)
- {
- f1 <- function (x)
- {
- x
- }
- f1(x) - 1L
- }
- exp(f1(x))
-}
-<environment: 0x90d97e4>
-
-[[2]]
-function (x)
-{
- f1 <- function (x)
- {
- f1 <- function (x)
- {
- x^2
- }
- f1(x) - 2L
- }
- exp(f1(x))
-}
-<environment: 0x90d97e4>
-\end{Soutput}
-\begin{Sinput}
-> (Y <- RealRandVariable(Map = list(function(x) {
-+ sin(x)
-+ }, function(x) {
-+ cos(x)
-+ }), Domain = Reals(), Range = Reals()))
-\end{Sinput}
-\begin{Soutput}
-An object of class “RealRandVariable”
-length of Map: 2
-Domain: Real Space with dimension 1
-Range: Real Space with dimension 1
-\end{Soutput}
-\begin{Sinput}
-> Map(Y)
-\end{Sinput}
-\begin{Soutput}
-[[1]]
-function (x)
-{
- sin(x)
-}
-
-[[2]]
-function (x)
-{
- cos(x)
-}
-\end{Soutput}
-\begin{Sinput}
-> R3 <- X %*% Y
-> dimension(R3)
-\end{Sinput}
-\begin{Soutput}
-[1] 1
-\end{Soutput}
-\begin{Sinput}
-> 2 * sin(2) + 2^2 * cos(2)
-\end{Sinput}
-\begin{Soutput}
-[1] 0.1540075
-\end{Soutput}
-\begin{Sinput}
-> (R4 <- X %*% t(Y))
-\end{Sinput}
-\begin{Soutput}
-An object of class “EuclRandMatrix”
-Dim of Map: 2 2
-Domain: Real Space with dimension 1
-Range: Euclidean Space with dimension 1
-\end{Soutput}
-\begin{Sinput}
-> dimension(R4)
-\end{Sinput}
-\begin{Soutput}
-[1] 4
-\end{Soutput}
-\begin{Sinput}
-> (M <- matrix(c(2 * sin(2), 2^2 * sin(2), 2 * cos(2), 2^2 * cos(2)),
-+ ncol = 2))
-\end{Sinput}
-\begin{Soutput}
- [,1] [,2]
-[1,] 1.818595 -0.8322937
-[2,] 3.637190 -1.6645873
-\end{Soutput}
-\begin{Sinput}
-> (R5 <- M %*% R4)
-\end{Sinput}
-\begin{Soutput}
-An object of class “EuclRandMatrix”
-Dim of Map: 2 2
-Domain: Real Space with dimension 1
-Range: Real Space with dimension 1
-\end{Soutput}
-\end{Schunk}
-We also implemented {\tt S4} methods for the generic function {\tt E} of
-package {\tt distrEx}~\cite{distr}. That is, given some distribution {\tt D},
-respectively some conditional distribution {\tt CD} and some random variable {\tt X}
-we can compute the (conditional) expectation of {\tt X} under {\tt D}, respectively
-{\tt CD} simply by
-\begin{Schunk}
-\begin{Sinput}
-> D <- Norm()
-> E(object = D, fun = X)
-\end{Sinput}
-\begin{Soutput}
-[1] 2.587378e-16 9.999942e-01
-\end{Soutput}
-\begin{Sinput}
-> E(D)
-\end{Sinput}
-\begin{Soutput}
-[1] 0
-\end{Soutput}
-\begin{Sinput}
-> var(D)
-\end{Sinput}
-\begin{Soutput}
-[1] 1
-\end{Soutput}
-\begin{Sinput}
-> (CD <- LMCondDistribution(theta = 1))
-\end{Sinput}
-\begin{Soutput}
-Distribution object of class: AbscontCondDistribution
-theta : 1
-intercept : 0
-scale : 1
-## cond:
-name: conditioning by an Euclidean space
-Range: Euclidean Space with dimension 1
-\end{Soutput}
-\begin{Sinput}
-> E(object = CD, fun = X, cond = 2)
-\end{Sinput}
-\begin{Soutput}
-[1] 2.000000 4.999993
-\end{Soutput}
-\begin{Sinput}
-> E(Norm(mean = 2))
-\end{Sinput}
-\begin{Soutput}
-[1] 2
-\end{Soutput}
-\begin{Sinput}
-> E(Norm(mean = 2), fun = function(x) {
-+ x^2
-+ })
-\end{Sinput}
-\begin{Soutput}
-[1] 4.999993
-\end{Soutput}
-\end{Schunk}
-for some given condition {\tt cond}.
-% -----------------------------------------------------------------------
-\par
-In addition, we define methods for the generic function {\tt show} for the classes
-{\tt RandVariable}, {\tt EuclRandMatrix} and {\tt EuclRandVarList}. There are
-also methods for the generic functions {\tt dimension} (see package
-{\tt distr}~\cite{distr}), {\tt length}, {\tt ncol}, {\tt nrow}, {\tt t} and
-{\tt [} (cf.\ package {\tt base}). For more details we refer to the corresponding
-help pages.
-% -----------------------------------------------------------------------
-\par
-Finally, we introduce several new generic functions. A brief description
-of these functions is given in Table~\ref{ap.Rpack.RandVar.tab}.
-% -----------------------------------------------------------------------
-\begin{table}[!ht]
-\begin{center}
-\begin{tabular}{p{3.5cm}|p{8cm}}
- \textbf{Generic Function} & \textbf{Description} \\ \hline\hline
- \texttt{\%m\%} & matrix multiplication for {\tt EuclRandVarList}s \\ \hline
- \texttt{compatibleDomains} & test if the domains of two random variables
- are compatible \\ \hline
- \texttt{evalRandVar} & evaluation of random variables\\ \hline
- \texttt{imageDistr} & image distribution of some distribution under some
- random variable \\ \hline
- \texttt{numberOfMaps} & number of functions contained in the slots {\tt Map}
- of the members of a {\tt EuclRandVarList}
-\end{tabular}
-\caption[New Generic Functions of Package {\tt RandVar}]
-{New generic functions of package {\tt RandVar} (without accessor
-and replacement functions).}\label{ap.Rpack.RandVar.tab}%
-\end{center}
-\end{table}
-% -----------------------------------------------------------------------
-\par\noindent
-For more details about the full functionality of package {\tt RandVar}
-we refer to the source code and the corresponding help pages, respectively.
-% -----------------------------------------------------------------------
-\section{Odds and Ends}
-% -----------------------------------------------------------------------
-The main issue is to reduce the computation time for methods using
-objects of class {\tt RandVariable} and its subclasses as these classes
-play an important role in the computation of optimally robust
-estimators; confer Kohl~(2005)~\cite{MK:05}.
-In particular, we are looking for ways to increase the computation speed
-of {\tt evalRandVar} and {\tt E}.
-%-------------------------------------------------------------------------------
-\begin{thebibliography}{8}
-
-\bibitem{Cham:98}
-Chambers J.M.
-\newblock {\em {Programming with data. A guide to the S language}\/}.
-\newblock {Springer}.
-\newblock http://cm.bell-labs.com/stat/Sbook/index.html
-
-\bibitem{Gent:03}
-Gentleman R.
-\newblock {\em Object Orientated Programming. Slides of a Short Course held in Auckland\/}.
-\newblock http://www.stat.auckland.ac.nz/S-Workshop/Gentleman/Methods.pdf
-
-\bibitem{MK:05}
-Kohl M.
-\newblock {\em Numerical Contributions to the Asymptotic Theory of Robustness\/}.
-\newblock {Dissertation}, Universit\"at Bayreuth.
-\newblock See also http://stamats.de/ThesisMKohl.pdf
-
-\bibitem{distr}
-Ruckdeschel P., Kohl M., Stabla T., and Camphausen F.
-\newblock {S4 Classes for Distributions.}
-\newblock {\em R-News\/}, {\bf 6}(2): 10--13.
-\newblock http://CRAN.R-project.org/doc/Rnews/Rnews\_2006-2.pdf
-\newblock See also {http://www.uni-bayreuth.de/departments/math/org/mathe7/RUCKDESCHEL/pubs/distr.pdf}
-
-\end{thebibliography}
-% -------------------------------------------------------------------------------
-\end{document}
-% -------------------------------------------------------------------------------
Deleted: branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.toc
===================================================================
--- branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.toc 2008-07-21 12:00:24 UTC (rev 107)
+++ branches/robast-0.6/pkg/RandVar/inst/doc/RandVar.toc 2008-07-21 12:01:18 UTC (rev 108)
@@ -1,3 +0,0 @@
-\contentsline {section}{\numberline {1}{\tt S4} Classes}{2}{section.1}
-\contentsline {section}{\numberline {2}Functions and Methods}{3}{section.2}
-\contentsline {section}{\numberline {3}Odds and Ends}{9}{section.3}
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