[Robast-commits] r75 - in pkg: ROptEst/chm RandVar/R RandVar/chm RandVar/man RobAStBase/chm RobLox RobLox/chm
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Tue Feb 26 20:26:58 CET 2008
Author: ruckdeschel
Date: 2008-02-26 20:26:57 +0100 (Tue, 26 Feb 2008)
New Revision: 75
Added:
pkg/RandVar/R/util.R
pkg/RandVar/chm/util.html
pkg/RandVar/man/util.Rd
pkg/RobAStBase/chm/optIC.html
pkg/RobLox/chm/
pkg/RobLox/chm/00Index.html
pkg/RobLox/chm/Rchm.css
pkg/RobLox/chm/RobLox.chm
pkg/RobLox/chm/RobLox.hhp
pkg/RobLox/chm/RobLox.toc
pkg/RobLox/chm/logo.jpg
pkg/RobLox/chm/rlOptIC.html
pkg/RobLox/chm/rlsOptIC.AL.html
pkg/RobLox/chm/rlsOptIC.An1.html
pkg/RobLox/chm/rlsOptIC.An2.html
pkg/RobLox/chm/rlsOptIC.AnMad.html
pkg/RobLox/chm/rlsOptIC.BM.html
pkg/RobLox/chm/rlsOptIC.Ha3.html
pkg/RobLox/chm/rlsOptIC.Ha4.html
pkg/RobLox/chm/rlsOptIC.HaMad.html
pkg/RobLox/chm/rlsOptIC.Hu1.html
pkg/RobLox/chm/rlsOptIC.Hu2.html
pkg/RobLox/chm/rlsOptIC.Hu2a.html
pkg/RobLox/chm/rlsOptIC.Hu3.html
pkg/RobLox/chm/rlsOptIC.HuMad.html
pkg/RobLox/chm/rlsOptIC.M.html
pkg/RobLox/chm/rlsOptIC.MM2.html
pkg/RobLox/chm/rlsOptIC.Tu1.html
pkg/RobLox/chm/rlsOptIC.Tu2.html
pkg/RobLox/chm/rlsOptIC.TuMad.html
pkg/RobLox/chm/roblox.html
pkg/RobLox/chm/rowRoblox.html
pkg/RobLox/chm/rsOptIC.html
Modified:
pkg/ROptEst/chm/00Index.html
pkg/ROptEst/chm/ROptEst.hhp
pkg/ROptEst/chm/ROptEst.toc
pkg/RandVar/R/EuclRandVarList.R
pkg/RandVar/R/EuclRandVariable.R
pkg/RandVar/chm/RandVar.chm
pkg/RandVar/chm/RandVar.hhp
pkg/RandVar/chm/RandVar.toc
Log:
new: util.R -- for determining image distribution of distr under f even if f(distr) fails (unsafe however; does not check for point masses!!)
Modified: pkg/ROptEst/chm/00Index.html
===================================================================
--- pkg/ROptEst/chm/00Index.html 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/ROptEst/chm/00Index.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -220,12 +220,6 @@
<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
<tr><td width="25%"><a href="leastFavorableRadius.html">leastFavorableRadius-methods</a></td>
<td>Generic Function for the Computation of Least Favorable Radii</td></tr>
-<tr><td width="25%"><a href="locMEstimator.html">locMEstimator</a></td>
-<td>Generic function for the computation of location M estimators</td></tr>
-<tr><td width="25%"><a href="locMEstimator.html">locMEstimator,numeric,InfluenceCurve-method</a></td>
-<td>Generic function for the computation of location M estimators</td></tr>
-<tr><td width="25%"><a href="locMEstimator.html">locMEstimator-methods</a></td>
-<td>Generic function for the computation of location M estimators</td></tr>
<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius</a></td>
<td>Computation of the lower case radius</td></tr>
<tr><td width="25%"><a href="lowerCaseRadius.html">lowerCaseRadius,L2ParamFamily,ContNeighborhood,asMSE,ANY-method</a></td>
Modified: pkg/ROptEst/chm/ROptEst.hhp
===================================================================
--- pkg/ROptEst/chm/ROptEst.hhp 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/ROptEst/chm/ROptEst.hhp 2008-02-26 19:26:57 UTC (rev 75)
@@ -27,7 +27,6 @@
getL2normL2deriv.html
getRiskIC.html
leastFavorableRadius.html
-locMEstimator.html
lowerCaseRadius.html
minmaxBias.html
optIC.html
Modified: pkg/ROptEst/chm/ROptEst.toc
===================================================================
--- pkg/ROptEst/chm/ROptEst.toc 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/ROptEst/chm/ROptEst.toc 2008-02-26 19:26:57 UTC (rev 75)
@@ -390,18 +390,6 @@
<param name="Local" value="leastFavorableRadius.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="locMEstimator">
-<param name="Local" value="locMEstimator.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="locMEstimator,numeric,InfluenceCurve-method">
-<param name="Local" value="locMEstimator.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="locMEstimator-methods">
-<param name="Local" value="locMEstimator.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="lowerCaseRadius">
<param name="Local" value="lowerCaseRadius.html">
</OBJECT>
@@ -543,10 +531,6 @@
<param name="Local" value="leastFavorableRadius.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
-<param name="Name" value="Generic function for the computation of location M estimators">
-<param name="Local" value="locMEstimator.html">
-</OBJECT>
-<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Generic function for the computation of optimally robust ICs">
<param name="Local" value="optIC.html">
</OBJECT>
Modified: pkg/RandVar/R/EuclRandVarList.R
===================================================================
--- pkg/RandVar/R/EuclRandVarList.R 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/RandVar/R/EuclRandVarList.R 2008-02-26 19:26:57 UTC (rev 75)
@@ -113,7 +113,7 @@
for(i in 1:nrvalues1){
for(j in 1:length(RandVar[[i]])){
comp <- comp + 1
- res[[comp]] <- RandVar[[i]]@Map[[j]](distr)
+ res[[comp]] <- .getImageDistr(f = RandVar[[i]]@Map[[j]], distr)
}
}
Modified: pkg/RandVar/R/EuclRandVariable.R
===================================================================
--- pkg/RandVar/R/EuclRandVariable.R 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/RandVar/R/EuclRandVariable.R 2008-02-26 19:26:57 UTC (rev 75)
@@ -327,8 +327,7 @@
nrvalues <- length(RandVar)
res <- vector(mode = "list", length = nrvalues)
for(i in 1:nrvalues)
- res[[i]] <- RandVar at Map[[i]](distr)
-
+ res[[i]] <- .getImageDistr(f = RandVar at Map[[i]], distr)
return(new("DistrList", res))
})
Added: pkg/RandVar/R/util.R
===================================================================
--- pkg/RandVar/R/util.R (rev 0)
+++ pkg/RandVar/R/util.R 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,9 @@
+## small util if imageDistr fails
+.getImageDistr <- function(f, distr)
+{ if (is(try(return(f(distr)), silent = TRUE),
+ "try-error")){
+ rl <- function(n) { xr <- r(distr)(n); f(xr) }
+ dr <- RtoDPQ(r = rl)
+ return(new("AbscontDistribution", d = dr$dfun,
+ r = rl, p = dr$pfun, q = dr$qfun, .withSim = TRUE))}
+}
\ No newline at end of file
Modified: pkg/RandVar/chm/RandVar.chm
===================================================================
(Binary files differ)
Modified: pkg/RandVar/chm/RandVar.hhp
===================================================================
--- pkg/RandVar/chm/RandVar.hhp 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/RandVar/chm/RandVar.hhp 2008-02-26 19:26:57 UTC (rev 75)
@@ -24,3 +24,4 @@
RandVariable.html
RealRandVariable-class.html
RealRandVariable.html
+util.html
Modified: pkg/RandVar/chm/RandVar.toc
===================================================================
--- pkg/RandVar/chm/RandVar.toc 2008-02-26 13:38:57 UTC (rev 74)
+++ pkg/RandVar/chm/RandVar.toc 2008-02-26 19:26:57 UTC (rev 75)
@@ -78,6 +78,10 @@
<param name="Local" value="EuclRandVarList-class.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value=".getImageDistr">
+<param name="Local" value="util.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Arith,EuclRandMatrix,EuclRandMatrix-method">
<param name="Local" value="EuclRandMatrix-class.html">
</OBJECT>
@@ -523,6 +527,10 @@
<param name="Local" value="RealRandVariable.html">
</OBJECT>
<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Help function for generation of image distributions">
+<param name="Local" value="util.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
<param name="Name" value="Implementation of random variables ">
<param name="Local" value="RandVar-package.html">
</OBJECT>
Added: pkg/RandVar/chm/util.html
===================================================================
--- pkg/RandVar/chm/util.html (rev 0)
+++ pkg/RandVar/chm/util.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,72 @@
+<html><head><title>Help function for generation of image distributions</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>.getImageDistr(RandVar)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: .getImageDistr">
+<param name="keyword" value=" Help function for generation of image distributions">
+</object>
+
+
+<h2>Help function for generation of image distributions</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generates an imageDistribution f(distr).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+.getImageDistr(f, distr)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>f</code></td>
+<td>
+a function with values in R</td></tr>
+<tr valign="top"><td><code>distr</code></td>
+<td>
+an object of class <code>"Abscontdistribution"</code> </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+works even if <code>f(distr)</code> fails;
+if anything else fails does simulations of <code>f(x)</code>,
+<code>x</code> according to <code>distr</code>; uses <code>RtoDPQ</code> then;
+does not check whether <code>f(distr)</code> has point masses
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+image distribution of <code>distr</code> under <code>f</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Peter Ruckdeschel <a href="mailto:Peter.Ruckdeschel at uni-bayreuth.de">Peter.Ruckdeschel at uni-bayreuth.de</a>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RandVar</em> version 0.6.2 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RandVar/man/util.Rd
===================================================================
--- pkg/RandVar/man/util.Rd (rev 0)
+++ pkg/RandVar/man/util.Rd 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,27 @@
+\name{.getImageDistr}
+\alias{.getImageDistr}
+
+\title{Help function for generation of image distributions}
+\description{
+ Generates an imageDistribution f(distr).
+}
+\usage{
+.getImageDistr(f, distr)
+}
+\arguments{
+ \item{f}{a function with values in R}
+ \item{distr}{an object of class \code{"Abscontdistribution"} }
+}
+\value{image distribution of \code{distr} under \code{f}}
+\details{works even if \code{f(distr)} fails;
+ if anything else fails does simulations of \code{f(x)},
+ \code{x} according to \code{distr}; uses \code{RtoDPQ} then;
+ does not check whether \code{f(distr)} has point masses}
+%\references{}
+\author{Peter Ruckdeschel \email{Peter.Ruckdeschel at uni-bayreuth.de}}
+%\note{}
+\examples{
+}
+\concept{image distribution}
+\concept{random variable}
+\keyword{internal}
Added: pkg/RobAStBase/chm/optIC.html
===================================================================
--- pkg/RobAStBase/chm/optIC.html (rev 0)
+++ pkg/RobAStBase/chm/optIC.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,119 @@
+<html><head><title>Generic function for the computation of optimally robust ICs</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>optIC(RobAStBase)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: optIC">
+<param name="keyword" value="R: optIC-methods">
+<param name="keyword" value="R: optIC,L2ParamFamily,asCov-method">
+<param name="keyword" value=" Generic function for the computation of optimally robust ICs">
+</object>
+
+
+<h2>Generic function for the computation of optimally robust ICs</h2>
+
+
+<h3>Description</h3>
+
+<p>
+Generic function for the computation of optimally robust ICs.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+optIC(model, risk, ...)
+
+## S4 method for signature 'L2ParamFamily, asCov':
+optIC(model, risk)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>model</code></td>
+<td>
+probability model. </td></tr>
+<tr valign="top"><td><code>risk</code></td>
+<td>
+object of class <code>"RiskType"</code>. </td></tr>
+<tr valign="top"><td><code>...</code></td>
+<td>
+additional parameters. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The classical optimal IC which ist optimal in sense of the Cramer-Rao bound
+is computed.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Some optimally robust IC is computed.</p>
+
+<h3>Methods</h3>
+
+<dl>
+<dt>model = "L2ParamFamily", risk = "asCov"</dt><dd>computes
+classical optimal influence curve for L2 differentiable
+parametric families.</dd>
+</dl>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="InfluenceCurve-class.html">InfluenceCurve-class</a></code>, <code><a onclick="findlink('distrMod', 'RiskType-class.html')" style="text-decoration: underline; color: blue; cursor: hand">RiskType-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+B <- BinomFamily(size = 25, prob = 0.25)
+
+## classical optimal IC
+IC0 <- optIC(model = B, risk = asCov())
+plot(IC0) # plot IC
+checkIC(IC0, B)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobAStBase</em> version 0.1.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/00Index.html
===================================================================
--- pkg/RobLox/chm/00Index.html (rev 0)
+++ pkg/RobLox/chm/00Index.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,64 @@
+<html><head><title>Optimally robust influence curves for location and scale</title>
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head><body>
+<h1>Optimally robust influence curves for location and scale
+<img class="toplogo" src="logo.jpg" alt="[R logo]"></h1>
+
+<hr>
+
+<object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value=".. contents">
+</object>
+
+<h2>Help pages for package ‘RobLox’ version 0.6.0</h2>
+
+
+<table width="100%">
+<tr><td width="25%"><a href="rowRoblox.html">colRoblox</a></td>
+<td>Optimally robust estimator for location and/or scale</td></tr>
+<tr><td width="25%"><a href="rlOptIC.html">rlOptIC</a></td>
+<td>Computation of the optimally robust IC for AL estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.AL.html">rlsOptIC.AL</a></td>
+<td>Computation of the optimally robust IC for AL estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.An1.html">rlsOptIC.An1</a></td>
+<td>Computation of the optimally robust IC for An1 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.An2.html">rlsOptIC.An2</a></td>
+<td>Computation of the optimally robust IC for An2 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.AnMad.html">rlsOptIC.AnMad</a></td>
+<td>Computation of the optimally robust IC for AnMad estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.BM.html">rlsOptIC.BM</a></td>
+<td>Computation of the optimally robust IC for BM estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Ha3.html">rlsOptIC.Ha3</a></td>
+<td>Computation of the optimally robust IC for Ha3 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Ha4.html">rlsOptIC.Ha4</a></td>
+<td>Computation of the optimally robust IC for Ha4 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.HaMad.html">rlsOptIC.HaMad</a></td>
+<td>Computation of the optimally robust IC for HuMad estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Hu1.html">rlsOptIC.Hu1</a></td>
+<td>Computation of the optimally robust IC for Hu1 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Hu2.html">rlsOptIC.Hu2</a></td>
+<td>Computation of the optimally robust IC for Hu2 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Hu2a.html">rlsOptIC.Hu2a</a></td>
+<td>Computation of the optimally robust IC for Hu2a estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Hu3.html">rlsOptIC.Hu3</a></td>
+<td>Computation of the optimally robust IC for Hu3 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.HuMad.html">rlsOptIC.HuMad</a></td>
+<td>Computation of the optimally robust IC for HuMad estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.M.html">rlsOptIC.M</a></td>
+<td>Computation of the optimally robust IC for M estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.MM2.html">rlsOptIC.MM2</a></td>
+<td>Computation of the optimally robust IC for MM2 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Tu1.html">rlsOptIC.Tu1</a></td>
+<td>Computation of the optimally robust IC for Tu1 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.Tu2.html">rlsOptIC.Tu2</a></td>
+<td>Computation of the optimally robust IC for Tu2 estimators</td></tr>
+<tr><td width="25%"><a href="rlsOptIC.TuMad.html">rlsOptIC.TuMad</a></td>
+<td>Computation of the optimally robust IC for TuMad estimators</td></tr>
+<tr><td width="25%"><a href="roblox.html">roblox</a></td>
+<td>Optimally robust estimator for location and/or scale</td></tr>
+<tr><td width="25%"><a href="rowRoblox.html">rowRoblox</a></td>
+<td>Optimally robust estimator for location and/or scale</td></tr>
+<tr><td width="25%"><a href="rsOptIC.html">rsOptIC</a></td>
+<td>Computation of the optimally robust IC for AL estimators</td></tr>
+</table>
+</body></html>
Added: pkg/RobLox/chm/Rchm.css
===================================================================
--- pkg/RobLox/chm/Rchm.css (rev 0)
+++ pkg/RobLox/chm/Rchm.css 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,31 @@
+BODY{ background: white;
+ color: black }
+
+A:link{ background: white;
+ color: blue }
+A:visited{ background: white;
+ color: rgb(50%, 0%, 50%) }
+
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+ color: rgb(55%, 55%, 55%);
+ font-family: monospace;
+ font-size: large;
+ text-align: center }
+
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+ color: rgb(0%, 0%, 100%);
+ font-family: monospace;
+ text-align: center }
+
+H3{ background: white;
+ color: rgb(40%, 40%, 40%);
+ font-family: monospace }
+
+IMG.toplogo{ vertical-align: middle }
+
+span.acronym{font-size: small}
+span.env{font-family: monospace}
+span.file{font-family: monospace}
+span.option{font-family: monospace}
+span.pkg{font-weight: bold}
+span.samp{font-family: monospace}
Added: pkg/RobLox/chm/RobLox.chm
===================================================================
(Binary files differ)
Property changes on: pkg/RobLox/chm/RobLox.chm
___________________________________________________________________
Name: svn:mime-type
+ application/octet-stream
Added: pkg/RobLox/chm/RobLox.hhp
===================================================================
--- pkg/RobLox/chm/RobLox.hhp (rev 0)
+++ pkg/RobLox/chm/RobLox.hhp 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,36 @@
+[OPTIONS]
+Auto Index=Yes
+Contents file=RobLox.toc
+Compatibility=1.1 or later
+Compiled file=RobLox.chm
+Default topic=00Index.html
+Display compile progress=No
+Full-text search=Yes
+Full text search stop list file=..\..\..\gnuwin32\help\R.stp
+Title=R Help for package RobLox
+
+
+[FILES]
+00Index.html
+rlOptIC.html
+rlsOptIC.AL.html
+rlsOptIC.An1.html
+rlsOptIC.An2.html
+rlsOptIC.AnMad.html
+rlsOptIC.BM.html
+rlsOptIC.Ha3.html
+rlsOptIC.Ha4.html
+rlsOptIC.HaMad.html
+rlsOptIC.Hu1.html
+rlsOptIC.Hu2.html
+rlsOptIC.Hu2a.html
+rlsOptIC.Hu3.html
+rlsOptIC.HuMad.html
+rlsOptIC.M.html
+rlsOptIC.MM2.html
+rlsOptIC.Tu1.html
+rlsOptIC.Tu2.html
+rlsOptIC.TuMad.html
+roblox.html
+rowRoblox.html
+rsOptIC.html
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@@ -0,0 +1,183 @@
+<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML//EN">
+<HEAD></HEAD><HTML><BODY>
+<UL>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Package RobLox: Contents">
+<param name="Local" value="00Index.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Package RobLox: R objects">
+</OBJECT>
+<UL>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="colRoblox">
+<param name="Local" value="rowRoblox.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlOptIC">
+<param name="Local" value="rlOptIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.AL">
+<param name="Local" value="rlsOptIC.AL.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.An1">
+<param name="Local" value="rlsOptIC.An1.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.An2">
+<param name="Local" value="rlsOptIC.An2.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.AnMad">
+<param name="Local" value="rlsOptIC.AnMad.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.BM">
+<param name="Local" value="rlsOptIC.BM.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Ha3">
+<param name="Local" value="rlsOptIC.Ha3.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Ha4">
+<param name="Local" value="rlsOptIC.Ha4.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.HaMad">
+<param name="Local" value="rlsOptIC.HaMad.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Hu1">
+<param name="Local" value="rlsOptIC.Hu1.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Hu2">
+<param name="Local" value="rlsOptIC.Hu2.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Hu2a">
+<param name="Local" value="rlsOptIC.Hu2a.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Hu3">
+<param name="Local" value="rlsOptIC.Hu3.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.HuMad">
+<param name="Local" value="rlsOptIC.HuMad.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.M">
+<param name="Local" value="rlsOptIC.M.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.MM2">
+<param name="Local" value="rlsOptIC.MM2.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Tu1">
+<param name="Local" value="rlsOptIC.Tu1.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rlsOptIC.Tu2">
+<param name="Local" value="rlsOptIC.Tu2.html">
+</OBJECT>
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+<param name="Name" value="rlsOptIC.TuMad">
+<param name="Local" value="rlsOptIC.TuMad.html">
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+<param name="Name" value="roblox">
+<param name="Local" value="roblox.html">
+</OBJECT>
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+<param name="Name" value="rowRoblox">
+<param name="Local" value="rowRoblox.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="rsOptIC">
+<param name="Local" value="rsOptIC.html">
+</OBJECT>
+</UL>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Package RobLox: Titles">
+</OBJECT>
+<UL>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for AL estimators">
+<param name="Local" value="rsOptIC.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for An1 estimators">
+<param name="Local" value="rlsOptIC.An1.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for An2 estimators">
+<param name="Local" value="rlsOptIC.An2.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for AnMad estimators">
+<param name="Local" value="rlsOptIC.AnMad.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for BM estimators">
+<param name="Local" value="rlsOptIC.BM.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Ha3 estimators">
+<param name="Local" value="rlsOptIC.Ha3.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Ha4 estimators">
+<param name="Local" value="rlsOptIC.Ha4.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Hu1 estimators">
+<param name="Local" value="rlsOptIC.Hu1.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Hu2 estimators">
+<param name="Local" value="rlsOptIC.Hu2.html">
+</OBJECT>
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+<param name="Name" value="Computation of the optimally robust IC for Hu2a estimators">
+<param name="Local" value="rlsOptIC.Hu2a.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Hu3 estimators">
+<param name="Local" value="rlsOptIC.Hu3.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for HuMad estimators">
+<param name="Local" value="rlsOptIC.HuMad.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for M estimators">
+<param name="Local" value="rlsOptIC.M.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for MM2 estimators">
+<param name="Local" value="rlsOptIC.MM2.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Tu1 estimators">
+<param name="Local" value="rlsOptIC.Tu1.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for Tu2 estimators">
+<param name="Local" value="rlsOptIC.Tu2.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Computation of the optimally robust IC for TuMad estimators">
+<param name="Local" value="rlsOptIC.TuMad.html">
+</OBJECT>
+<LI> <OBJECT type="text/sitemap">
+<param name="Name" value="Optimally robust estimator for location and/or scale">
+<param name="Local" value="rowRoblox.html">
+</OBJECT>
+</UL>
+</UL>
+</BODY></HTML>
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+ application/octet-stream
Added: pkg/RobLox/chm/rlOptIC.html
===================================================================
--- pkg/RobLox/chm/rlOptIC.html (rev 0)
+++ pkg/RobLox/chm/rlOptIC.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,132 @@
+<html><head><title>Computation of the optimally robust IC for AL estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlOptIC(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlOptIC">
+<param name="keyword" value=" Computation of the optimally robust IC for AL estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for AL estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlOptIC</code> computes the optimally robust IC for
+AL estimators in case of normal location and (convex) contamination
+neighborhoods. The definition of these estimators can be found
+in Rieder (1994) or Kohl (2005), respectively.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlOptIC(r, mean = 0, sd = 1, bUp = 1000, computeIC = TRUE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>mean</code></td>
+<td>
+specified mean.</td></tr>
+<tr valign="top"><td><code>sd</code></td>
+<td>
+specified standard deviation.</td></tr>
+<tr valign="top"><td><code>bUp</code></td>
+<td>
+positive real: the upper end point of the
+interval to be searched for the clipping bound b. </td></tr>
+<tr valign="top"><td><code>computeIC</code></td>
+<td>
+logical: should IC be computed. See details below. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+If 'computeIC' is 'FALSE' only the Lagrange multipliers 'A', 'a', and
+'b' contained in the optimally robust IC are computed.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+If 'computeIC' is 'TRUE' an object of class <code>"ContIC"</code> is returned,
+otherwise a list of Lagrane multipliers
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>A</code></td>
+<td>
+standardizing constant </td></tr>
+<tr valign="top"><td><code>a</code></td>
+<td>
+centering constant; always '= 0' is this symmetric setup </td></tr>
+<tr valign="top"><td><code>b</code></td>
+<td>
+optimal clipping bound </td></tr>
+</table>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a href="roblox.html">roblox</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlOptIC(r = 0.1)
+distrExOptions("ErelativeTolerance" = 1e-12)
+checkIC(IC1)
+distrExOptions("ErelativeTolerance" = .Machine$double.eps^0.25) # default
+Risks(IC1)
+cent(IC1)
+clip(IC1)
+stand(IC1)
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.AL.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.AL.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.AL.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,183 @@
+<html><head><title>Computation of the optimally robust IC for AL estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.AL(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.AL">
+<param name="keyword" value=" Computation of the optimally robust IC for AL estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for AL estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.AL</code> computes the optimally robust IC for
+AL estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Section 8.2 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.AL(r, mean = 0, sd = 1, A.loc.start = 1, a.sc.start = 0,
+ A.sc.start = 0.5, bUp = 1000, delta = 1e-6, itmax = 100,
+ check = FALSE, computeIC = TRUE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>mean</code></td>
+<td>
+specified mean.</td></tr>
+<tr valign="top"><td><code>sd</code></td>
+<td>
+specified standard deviation.</td></tr>
+<tr valign="top"><td><code>A.loc.start</code></td>
+<td>
+positive real: starting value for
+the standardizing constant of the location part. </td></tr>
+<tr valign="top"><td><code>a.sc.start</code></td>
+<td>
+real: starting value for centering
+constant of the scale part. </td></tr>
+<tr valign="top"><td><code>A.sc.start</code></td>
+<td>
+positive real: starting value for
+the standardizing constant of the scale part. </td></tr>
+<tr valign="top"><td><code>bUp</code></td>
+<td>
+positive real: the upper end point of the
+interval to be searched for the clipping bound b. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>itmax</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>check</code></td>
+<td>
+logical: should constraints be checked. </td></tr>
+<tr valign="top"><td><code>computeIC</code></td>
+<td>
+logical: should IC be computed. See details below. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The Lagrange multipliers contained in the expression
+of the optimally robust IC can be accessed via the
+accessor functions <code>cent</code>, <code>clip</code> and <code>stand</code>.
+If 'computeIC' is 'FALSE' only the Lagrange multipliers 'A', 'a',
+and 'b' contained in the optimally robust IC are computed.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+If 'computeIC' is 'TRUE' an object of class <code>"ContIC"</code> is returned,
+otherwise a list of Lagrane multipliers
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>A</code></td>
+<td>
+standardizing matrix </td></tr>
+<tr valign="top"><td><code>a</code></td>
+<td>
+centering vector </td></tr>
+<tr valign="top"><td><code>b</code></td>
+<td>
+optimal clipping bound </td></tr>
+</table>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a href="roblox.html">roblox</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.AL(r = 0.1, check = TRUE)
+distrExOptions("ErelativeTolerance" = 1e-12)
+checkIC(IC1)
+distrExOptions("ErelativeTolerance" = .Machine$double.eps^0.25) # default
+Risks(IC1)
+cent(IC1)
+clip(IC1)
+stand(IC1)
+plot(IC1)
+infoPlot(IC1)
+
+## one-step estimation
+## see also: ?roblox
+## 1. data: random sample
+ind <- rbinom(100, size=1, prob=0.05)
+x <- rnorm(100, mean=0, sd=(1-ind) + ind*9)
+mean(x)
+sd(x)
+median(x)
+mad(x)
+
+## 2. Kolmogorov(-Smirnov) minimum distance estimator
+## -> we use it as initial estimate for one-step construction
+(est0 <- MDEstimator(x, ParamFamily = NormLocationScaleFamily(), distance = KolmogorovDist))
+
+## 3. one-step estimation: radius known
+IC1 <- rlsOptIC.AL(r = 0.5, mean = est0$estimate[1], sd = est0$estimate[2])
+(est1 <- oneStepEstimator(x, IC1, est0$estimate))
+
+## 4. one-step estimation: radius unknown
+## take least favorable radius r = 0.579
+## cf. Table 8.1 in Kohl(2005)
+IC2 <- rlsOptIC.AL(r = 0.579, mean = est0$estimate[1], sd = est0$estimate[2])
+(est2 <- oneStepEstimator(x, IC2, est0$estimate))
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.An1.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.An1.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.An1.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,112 @@
+<html><head><title>Computation of the optimally robust IC for An1 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.An1(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.An1">
+<param name="keyword" value=" Computation of the optimally robust IC for An1 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for An1 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.An1</code> computes the optimally robust IC for
+An1 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.3 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.An1(r, aUp = 2.5, delta = 1e-06)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>aUp</code></td>
+<td>
+positive real: the upper end point of the interval
+to be searched for a. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal value of the tuning constant a can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J.,
+Rogers, W.H. and Tukey, J.W. (1972) <EM>Robust estimates of location</EM>.
+Princeton University Press.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.An1(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.An2.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.An2.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.An2.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,121 @@
+<html><head><title>Computation of the optimally robust IC for An2 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.An2(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.An2">
+<param name="keyword" value=" Computation of the optimally robust IC for An2 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for An2 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.An2</code> computes the optimally robust IC for
+An2 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.3 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.An2(r, a.start = 1.5, k.start = 1.5, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>a.start</code></td>
+<td>
+positive real: starting value for a. </td></tr>
+<tr valign="top"><td><code>k.start</code></td>
+<td>
+positive real: starting value for k. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if a or k are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for An2 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on a and k. The optimal values of the
+tuning constants a and k can be read off from the slot
+<code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J.,
+Rogers, W.H. and Tukey, J.W. (1972) <EM>Robust estimates of location</EM>.
+Princeton University Press.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.An2(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.AnMad.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.AnMad.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.AnMad.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,113 @@
+<html><head><title>Computation of the optimally robust IC for AnMad estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.AnMad(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.AnMad">
+<param name="keyword" value=" Computation of the optimally robust IC for AnMad estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for AnMad estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.AnMad</code> computes the optimally robust IC for
+AnMad estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators were
+considered in Andrews et al. (1972). A definition of these estimators
+can also be found in Subsection 8.5.3 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.AnMad(r, aUp = 2.5, delta = 1e-06)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>aUp</code></td>
+<td>
+positive real: the upper end point of the interval
+to be searched for a. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal value of the tuning constant a can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J.,
+Rogers, W.H. and Tukey, J.W. (1972) <EM>Robust estimates of location</EM>.
+Princeton University Press.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.AnMad(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.BM.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.BM.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.BM.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,124 @@
+<html><head><title>Computation of the optimally robust IC for BM estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.BM(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.BM">
+<param name="keyword" value=" Computation of the optimally robust IC for BM estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for BM estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.BM</code> computes the optimally robust IC for
+BM estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators were proposed
+by Bednarski and Mueller (2001). A definition of these
+estimators can also be found in Section 8.4 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.BM(r, bL.start = 2, bS.start = 1.5, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>bL.start</code></td>
+<td>
+positive real: starting value for <i>b_loc</i>. </td></tr>
+<tr valign="top"><td><code>bS.start</code></td>
+<td>
+positive real: starting value for <i>b_sc,0</i>. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if <i>b_loc</i> or <i>b_sc,0</i>
+are beyond the admitted values, <code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for BM estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on <i>b_loc</i>
+and <i>b_sc,0</i>. The optimal values of the
+tuning constants <i>b_loc</i>, <i>b_sc,0</i>,
+<i>alpha</i> and <i>gamma</i> can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Bednarski, T and Mueller, C.H. (2001) Optimal bounded influence
+regression and scale M-estimators in the context of experimental
+design. Statistics, <B>35</B>(4): 349–369.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.BM(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Ha3.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Ha3.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Ha3.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,120 @@
+<html><head><title>Computation of the optimally robust IC for Ha3 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Ha3(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Ha3">
+<param name="keyword" value=" Computation of the optimally robust IC for Ha3 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Ha3 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Ha3</code> computes the optimally robust IC for
+Ha3 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.2 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Ha3(r, a.start = 0.25, b.start = 2.5, c.start = 5,
+ delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>a.start</code></td>
+<td>
+positive real: starting value for a. </td></tr>
+<tr valign="top"><td><code>b.start</code></td>
+<td>
+positive real: starting value for b. </td></tr>
+<tr valign="top"><td><code>c.start</code></td>
+<td>
+positive real: starting value for c. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if a or b or c are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for Ha3 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on a, b and c. The optimal values of
+the tuning constants a, b and c can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Ha3(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Ha4.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Ha4.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Ha4.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,127 @@
+<html><head><title>Computation of the optimally robust IC for Ha4 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Ha4(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Ha4">
+<param name="keyword" value=" Computation of the optimally robust IC for Ha4 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Ha4 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Ha4</code> computes the optimally robust IC for
+Ha4 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.2 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Ha4(r, a.start = 0.25, b.start = 2.5, c.start = 5,
+ k.start = 1, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>a.start</code></td>
+<td>
+positive real: starting value for a. </td></tr>
+<tr valign="top"><td><code>b.start</code></td>
+<td>
+positive real: starting value for b. </td></tr>
+<tr valign="top"><td><code>c.start</code></td>
+<td>
+positive real: starting value for c. </td></tr>
+<tr valign="top"><td><code>k.start</code></td>
+<td>
+positive real: starting value for k. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if a or b or c or k are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for Ha4 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on a, b, c and k. The optimal values of
+the tuning constants a, b, c and k can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Marazzi, A. (1993) <EM>Algorithms, routines, and S functions
+for robust statistics</EM>. Wadsworth and Brooks / Cole.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Ha4(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.HaMad.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.HaMad.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.HaMad.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,126 @@
+<html><head><title>Computation of the optimally robust IC for HuMad estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.HaMad(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.HaMad">
+<param name="keyword" value=" Computation of the optimally robust IC for HuMad estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for HuMad estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.HuMad</code> computes the optimally robust IC for
+HuMad estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators were
+considered in Andrews et al. (1972). A definition of these estimators
+can also be found in Subsection 8.5.2 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.HaMad(r, a.start = 0.25, b.start = 2.5, c.start = 5,
+ delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>a.start</code></td>
+<td>
+positive real: starting value for a. </td></tr>
+<tr valign="top"><td><code>b.start</code></td>
+<td>
+positive real: starting value for b. </td></tr>
+<tr valign="top"><td><code>c.start</code></td>
+<td>
+positive real: starting value for c. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if a or b or c are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for HaMad estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on a, b and c. The optimal values of
+the tuning constants a, b, and c can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J.,
+Rogers, W.H. and Tukey, J.W. (1972) <EM>Robust estimates of location</EM>.
+Princeton University Press.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.HaMad(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Hu1.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Hu1.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Hu1.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,112 @@
+<html><head><title>Computation of the optimally robust IC for Hu1 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Hu1(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Hu1">
+<param name="keyword" value=" Computation of the optimally robust IC for Hu1 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Hu1 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Hu1</code> computes the optimally robust IC for
+Hu1 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators were
+proposed by Huber (1964), Proposal 2. A definition of these
+estimators can also be found in Subsection 8.5.1 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Hu1(r, kUp = 2.5, delta = 1e-06)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>kUp</code></td>
+<td>
+positive real: the upper end point of the interval
+to be searched for k. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal value of the tuning constant k can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1964) Robust estimation of a location parameter.
+Ann. Math. Stat. <B>35</B>: 73–101.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Hu1(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Hu2.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Hu2.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Hu2.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,120 @@
+<html><head><title>Computation of the optimally robust IC for Hu2 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Hu2(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Hu2">
+<param name="keyword" value=" Computation of the optimally robust IC for Hu2 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Hu2 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Hu2</code> computes the optimally robust IC for
+Hu2 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators were
+proposed in Example 6.4.1 of Huber (1981). A definition of these
+estimators can also be found in Subsection 8.5.1 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Hu2(r, k.start = 1.5, c.start = 1.5, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>k.start</code></td>
+<td>
+positive real: starting value for k. </td></tr>
+<tr valign="top"><td><code>c.start</code></td>
+<td>
+positive real: starting value for c. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if k1 or k2 are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for Hu2 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on k and c. The optimal values of
+the tuning constants k and c can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1981) <EM>Robust Statistics</EM>. New York: Wiley.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Hu2(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Hu2a.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Hu2a.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Hu2a.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,122 @@
+<html><head><title>Computation of the optimally robust IC for Hu2a estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Hu2a(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Hu2a">
+<param name="keyword" value=" Computation of the optimally robust IC for Hu2a estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Hu2a estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Hu2a</code> computes the optimally robust IC for
+Hu2a estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators are a
+simple modification of Huber (1964), Proposal 2 where we, in addition,
+admit a clipping from below. The definition of
+these estimators can be found in Subsection 8.5.1 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Hu2a(r, k1.start = 0.25, k2.start = 2.5, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>k1.start</code></td>
+<td>
+positive real: starting value for k1. </td></tr>
+<tr valign="top"><td><code>k2.start</code></td>
+<td>
+positive real: starting value for k2. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if k1 or k2 are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for Hu2a estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on k1 and k2. The optimal values of
+the tuning constants k1 and k2 can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1964) Robust estimation of a location parameter.
+Ann. Math. Stat. <B>35</B>: 73–101.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Hu2a(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Hu3.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Hu3.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Hu3.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,123 @@
+<html><head><title>Computation of the optimally robust IC for Hu3 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Hu3(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Hu3">
+<param name="keyword" value=" Computation of the optimally robust IC for Hu3 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Hu3 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Hu3</code> computes the optimally robust IC for
+Hu3 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.1 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Hu3(r, k.start = 1, c1.start = 0.1, c2.start = 0.5,
+ delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>k.start</code></td>
+<td>
+positive real: starting value for k. </td></tr>
+<tr valign="top"><td><code>c1.start</code></td>
+<td>
+positive real: starting value for c1. </td></tr>
+<tr valign="top"><td><code>c2.start</code></td>
+<td>
+positive real: starting value for c2. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if k or c1 or c2 are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for Hu2 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on k, c1 and c2. The optimal values of
+the tuning constants k, c1 and c2 can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1981) <EM>Robust Statistics</EM>. New York: Wiley.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Hu3(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.HuMad.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.HuMad.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.HuMad.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,113 @@
+<html><head><title>Computation of the optimally robust IC for HuMad estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.HuMad(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.HuMad">
+<param name="keyword" value=" Computation of the optimally robust IC for HuMad estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for HuMad estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.HuMad</code> computes the optimally robust IC for
+HuMad estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators were
+proposed by Andrews et al. (1972), p. 12. A definition of these
+estimators can also be found in Subsection 8.5.1 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.HuMad(r, kUp = 2.5, delta = 1e-06)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>kUp</code></td>
+<td>
+positive real: the upper end point of the interval
+to be searched for k. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal value of the tuning constant k can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J.,
+Rogers, W.H. and Tukey, J.W. (1972) <EM>Robust estimates of location</EM>.
+Princeton University Press.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.HuMad(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.M.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.M.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.M.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,134 @@
+<html><head><title>Computation of the optimally robust IC for M estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.M(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.M">
+<param name="keyword" value=" Computation of the optimally robust IC for M estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for M estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.M</code> computes the optimally robust IC for
+M estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Section 8.3 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.M(r, ggLo = 0.5, ggUp = 1.5, a1.start = 0.75, a3.start = 0.25,
+ bUp = 1000, delta = 1e-05, itmax = 100, check = FALSE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>ggLo</code></td>
+<td>
+non-negative real: the lower end point of the interval to be searched
+for <i>gamma</i>. </td></tr>
+<tr valign="top"><td><code>ggUp</code></td>
+<td>
+positive real: the upper end point of the interval to be searched
+for <i>gamma</i>. </td></tr>
+<tr valign="top"><td><code>a1.start</code></td>
+<td>
+real: starting value for <i>alpha_1</i>. </td></tr>
+<tr valign="top"><td><code>a3.start</code></td>
+<td>
+real: starting value for <i>alpha_3</i>. </td></tr>
+<tr valign="top"><td><code>bUp</code></td>
+<td>
+positive real: upper bound used in the
+computation of the optimal clipping bound b. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>itmax</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>check</code></td>
+<td>
+logical. Should constraints be checked. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal values of the tuning constants <i>alpha_1</i>,
+<i>alpha_3</i>, b and <i>gamma</i> can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Huber, P.J. (1981) <EM>Robust Statistics</EM>. New York: Wiley.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.M(r = 0.1, check = TRUE)
+distrExOptions("ErelativeTolerance" = 1e-12)
+checkIC(IC1, NormLocationScaleFamily())
+distrExOptions("ErelativeTolerance" = .Machine$double.eps^0.25)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.MM2.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.MM2.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.MM2.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,121 @@
+<html><head><title>Computation of the optimally robust IC for MM2 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.MM2(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.MM2">
+<param name="keyword" value=" Computation of the optimally robust IC for MM2 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for MM2 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.MM2</code> computes the optimally robust IC for
+MM2 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. These estimators are based
+on a proposal of Fraiman et al. (2001), p. 206. A definition of
+these estimators can also be found in Section 8.6 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.MM2(r, c.start = 1.5, d.start = 2, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>c.start</code></td>
+<td>
+positive real: starting value for c. </td></tr>
+<tr valign="top"><td><code>d.start</code></td>
+<td>
+positive real: starting value for d. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if a or k are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for MM2 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on c and d. The optimal values of
+the tuning constants c and d can be read off from the slot
+<code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Fraiman, R., Yohai, V.J. and Zamar, R.H. (2001) Optimal robust
+M-estimates of location. Ann. Stat. <B>29</B>(1): 194–223.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.MM2(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Tu1.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Tu1.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Tu1.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,112 @@
+<html><head><title>Computation of the optimally robust IC for Tu1 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Tu1(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Tu1">
+<param name="keyword" value=" Computation of the optimally robust IC for Tu1 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Tu1 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Tu1</code> computes the optimally robust IC for
+Tu1 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.4 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Tu1(r, aUp = 10, delta = 1e-06)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>aUp</code></td>
+<td>
+positive real: the upper end point of the interval
+to be searched for a. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal value of the tuning constant a can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Beaton, A.E. and Tukey, J.W. (1974) The fitting of power series,
+meaning polynomials, illustrated on band-spectroscopic data.
+Discussions. Technometrics <B>16</B>: 147–185.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Tu1(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.Tu2.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.Tu2.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.Tu2.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,121 @@
+<html><head><title>Computation of the optimally robust IC for Tu2 estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.Tu2(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.Tu2">
+<param name="keyword" value=" Computation of the optimally robust IC for Tu2 estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for Tu2 estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.Tu2</code> computes the optimally robust IC for
+Tu2 estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.4 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.Tu2(r, a.start = 5, k.start = 1.5, delta = 1e-06, MAX = 100)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>a.start</code></td>
+<td>
+positive real: starting value for a. </td></tr>
+<tr valign="top"><td><code>k.start</code></td>
+<td>
+positive real: starting value for k. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>MAX</code></td>
+<td>
+if a or k are beyond the admitted values,
+<code>MAX</code> is returned. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The computation of the optimally robust IC for Tu2 estimators
+is based on <code>optim</code> where <code>MAX</code> is used to
+control the constraints on a and k. The optimal values of
+the tuning constant a and k can be read off from the slot
+<code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Beaton, A.E. and Tukey, J.W. (1974) The fitting of power series,
+meaning polynomials, illustrated on band-spectroscopic data.
+Discussions. Technometrics <B>16</B>: 147–185.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.Tu2(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rlsOptIC.TuMad.html
===================================================================
--- pkg/RobLox/chm/rlsOptIC.TuMad.html (rev 0)
+++ pkg/RobLox/chm/rlsOptIC.TuMad.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,112 @@
+<html><head><title>Computation of the optimally robust IC for TuMad estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rlsOptIC.TuMad(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rlsOptIC.TuMad">
+<param name="keyword" value=" Computation of the optimally robust IC for TuMad estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for TuMad estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rlsOptIC.TuMad</code> computes the optimally robust IC for
+TuMad estimators in case of normal location with unknown scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Subsection 8.5.4 of Kohl (2005).
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rlsOptIC.TuMad(r, aUp = 10, delta = 1e-06)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>aUp</code></td>
+<td>
+positive real: the upper end point of the interval
+to be searched for a. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+The optimal value of the tuning constant a can be read off
+from the slot <code>Infos</code> of the resulting IC.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+Object of class <code>"IC"</code></p>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Beaton, A.E. and Tukey, J.W. (1974) The fitting of power series,
+meaning polynomials, illustrated on band-spectroscopic data.
+Discussions. Technometrics <B>16</B>: 147–185.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'IC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">IC-class</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rlsOptIC.TuMad(r = 0.1)
+checkIC(IC1)
+Risks(IC1)
+Infos(IC1)
+plot(IC1)
+infoPlot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/roblox.html
===================================================================
--- pkg/RobLox/chm/roblox.html (rev 0)
+++ pkg/RobLox/chm/roblox.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,237 @@
+<html><head><title>Optimally robust estimator for location and/or scale</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>roblox(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: roblox">
+<param name="keyword" value=" Optimally robust estimator for location and/or scale">
+</object>
+
+
+<h2>Optimally robust estimator for location and/or scale</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>roblox</code> computes the optimally robust estimator
+and corresponding IC for normal location und/or scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Rieder (1994) or Kohl (2005),
+respectively.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+roblox(x, mean, sd, eps, eps.lower, eps.upper, initial.est, k = 1, returnIC = FALSE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>x</code></td>
+<td>
+vector <code>x</code> of data values </td></tr>
+<tr valign="top"><td><code>mean</code></td>
+<td>
+specified mean.</td></tr>
+<tr valign="top"><td><code>sd</code></td>
+<td>
+specified standard deviation.</td></tr>
+<tr valign="top"><td><code>eps</code></td>
+<td>
+positive real (0 < <code>eps</code> <= 0.5): amount of gross errors.
+See details below. </td></tr>
+<tr valign="top"><td><code>eps.lower</code></td>
+<td>
+positive real (0 <= <code>eps.lower</code> <= <code>eps.upper</code>):
+lower bound for the amount of gross errors. See details below. </td></tr>
+<tr valign="top"><td><code>eps.upper</code></td>
+<td>
+positive real (<code>eps.lower</code> <= <code>eps.upper</code> <= 0.5):
+upper bound for the amount of gross errors. See details below. </td></tr>
+<tr valign="top"><td><code>initial.est</code></td>
+<td>
+initial estimate for <code>mean</code> and/or <code>sd</code>. If missing
+median and/or MAD are used. </td></tr>
+<tr valign="top"><td><code>k</code></td>
+<td>
+positive integer. k-step is used to compute the optimally robust estimator.</td></tr>
+<tr valign="top"><td><code>returnIC</code></td>
+<td>
+logical: should IC be returned. See details below. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+Computes the optimally robust estimator for location with scale specified,
+scale with location specified, or both if neither is specified. The computation
+uses a k-step construction with an appropriate initial estimate for location
+or scale or location and scale, respectively. Valid candidates are e.g.
+median and/or MAD (default) as well as Kolmogorov(-Smirnov) or von Mises minimum
+distance estimators; cf. Rieder (1994) and Kohl (2005).
+</p>
+<p>
+If the amount of gross errors (contamination) is known, it can be
+specified by <code>eps</code>. The radius of the corresponding infinitesimal
+contamination neighborhood is obtained by multiplying <code>eps</code>
+by the square root of the sample size.
+</p>
+<p>
+If the amount of gross errors (contamination) is unknown, try to find a
+rough estimate for the amount of gross errors, such that it lies
+between <code>eps.lower</code> and <code>eps.upper</code>.
+</p>
+<p>
+In case <code>eps.lower</code> is specified and <code>eps.upper</code> is missing,
+<code>eps.upper</code> is set to 0.5. In case <code>eps.upper</code> is specified and
+<code>eps.lower</code> is missing, <code>eps.lower</code> is set to 0.
+</p>
+<p>
+If neither <code>eps</code> nor <code>eps.lower</code> and/or <code>eps.upper</code> is
+specified, <code>eps.lower</code> and <code>eps.upper</code> are set to 0 and 0.5,
+respectively.
+</p>
+<p>
+If <code>eps</code> is missing, the radius-minimax estimator in sense of
+Rieder et al. (2001), respectively Section 2.2 of Kohl (2005) is returned.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+list of location and scale estimates
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>mean </code></td>
+<td>
+(estimated) mean</td></tr>
+<tr valign="top"><td><code>sd </code></td>
+<td>
+(estimated) sd </td></tr>
+<tr valign="top"><td><code>optIC</code></td>
+<td>
+object of class <code>"ContIC"</code>; optimally robust IC </td></tr>
+<tr valign="top"><td><code>contamination interval</code></td>
+<td>
+interval for the amount of gross errors </td></tr>
+<tr valign="top"><td><code>least favorable contamination</code></td>
+<td>
+amount of gross errors used for the computations </td></tr>
+<tr valign="top"><td><code>maximum MSE-inefficiency</code></td>
+<td>
+maximum (asymptotic) MSE-inefficiency </td></tr>
+</table>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+the Radius. Statistical Methods and Applications <EM>17</EM>(1) 13-40.
+</p>
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a href="rlOptIC.html">rlOptIC</a></code>,
+<code><a href="rsOptIC.html">rsOptIC</a></code>, <code><a href="rlsOptIC.AL.html">rlsOptIC.AL</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+ind <- rbinom(100, size=1, prob=0.05)
+x <- rnorm(100, mean=ind*3, sd=(1-ind) + ind*9)
+
+## amount of gross errors known
+res1 <- roblox(x, eps = 0.05, returnIC = TRUE)
+res1$mean
+res1$sd
+res1$optIC
+checkIC(res1$optIC)
+Risks(res1$optIC)
+Infos(res1$optIC)
+plot(res1$optIC)
+infoPlot(res1$optIC)
+
+## amount of gross errors unknown
+res2 <- roblox(x, eps.lower = 0.01, eps.upper = 0.1, returnIC = TRUE)
+res2$mean
+res2$sd
+res2$optIC
+checkIC(res2$optIC)
+Risks(res2$optIC)
+Infos(res2$optIC)
+plot(res2$optIC)
+infoPlot(res2$optIC)
+
+## estimator comparison
+# classical optimal (non-robust)
+c(mean(x), sd(x))
+
+# most robust
+c(median(x), mad(x))
+
+# optimally robust (amount of gross errors known)
+c(res1$mean, res1$sd)
+
+# optimally robust (amount of gross errors unknown)
+c(res2$mean, res2$sd)
+
+# Kolmogorov(-Smirnov) minimum distance estimator (robust)
+(ks.est <- MDEstimator(x, ParamFamily = NormLocationScaleFamily(), distance = KolmogorovDist))
+
+# optimally robust (amount of gross errors known)
+roblox(x, eps = 0.05, initial.est = ks.est$estimate)
+
+# Cramer von Mises minimum distance estimator (robust)
+(CvM.est <- MDEstimator(x, ParamFamily = NormLocationScaleFamily(), distance = CvMDist))
+
+# optimally robust (amount of gross errors known)
+roblox(x, eps = 0.05, initial.est = CvM.est$estimate)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rowRoblox.html
===================================================================
--- pkg/RobLox/chm/rowRoblox.html (rev 0)
+++ pkg/RobLox/chm/rowRoblox.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,210 @@
+<html><head><title>Optimally robust estimator for location and/or scale</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rowRoblox and colRoblox(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rowRoblox">
+<param name="keyword" value="R: colRoblox">
+<param name="keyword" value=" Optimally robust estimator for location and/or scale">
+</object>
+
+
+<h2>Optimally robust estimator for location and/or scale</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The functions <code>rowRoblox</code> and <code>colRoblox</code> compute
+the optimally robust estimator for normal location und/or scale and
+(convex) contamination neighborhoods. The definition of
+these estimators can be found in Rieder (1994) or Kohl (2005),
+respectively.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rowRoblox(x, mean, sd, eps, eps.lower, eps.upper, initial.est, k = 1)
+colRoblox(x, mean, sd, eps, eps.lower, eps.upper, initial.est, k = 1)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>x</code></td>
+<td>
+matrix <code>x</code> of data values </td></tr>
+<tr valign="top"><td><code>mean</code></td>
+<td>
+specified mean. See details below. </td></tr>
+<tr valign="top"><td><code>sd</code></td>
+<td>
+specified standard deviation. See details below. </td></tr>
+<tr valign="top"><td><code>eps</code></td>
+<td>
+positive real (0 < <code>eps</code> <= 0.5): amount of gross errors.
+See details below. </td></tr>
+<tr valign="top"><td><code>eps.lower</code></td>
+<td>
+positive real (0 <= <code>eps.lower</code> <= <code>eps.upper</code>):
+lower bound for the amount of gross errors. See details below. </td></tr>
+<tr valign="top"><td><code>eps.upper</code></td>
+<td>
+positive real (<code>eps.lower</code> <= <code>eps.upper</code> <= 0.5):
+upper bound for the amount of gross errors. See details below. </td></tr>
+<tr valign="top"><td><code>initial.est</code></td>
+<td>
+initial estimate for <code>mean</code> and/or <code>sd</code>. If missing
+median and/or MAD are used. </td></tr>
+<tr valign="top"><td><code>k</code></td>
+<td>
+positive integer. k-step is used to compute the optimally robust estimator.</td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+Computes the optimally robust estimator for location with scale specified,
+scale with location specified, or both if neither is specified. The computation
+uses a k-step construction with an appropriate initial estimate for location
+or scale or location and scale, respectively. Valid candidates are e.g.
+median and/or MAD (default) as well as Kolmogorov(-Smirnov) or von Mises minimum
+distance estimators; cf. Rieder (1994) and Kohl (2005).
+</p>
+<p>
+These functions are optimized for the situation where one has a matrix
+and wants to compute the optimally robust estimator for every row,
+respectively column of this matrix. In particular, the amount of cross
+errors is assumed to be constant for all rows, respectively columns.
+</p>
+<p>
+If the amount of gross errors (contamination) is known, it can be
+specified by <code>eps</code>. The radius of the corresponding infinitesimal
+contamination neighborhood is obtained by multiplying <code>eps</code>
+by the square root of the sample size.
+</p>
+<p>
+If the amount of gross errors (contamination) is unknown, try to find a
+rough estimate for the amount of gross errors, such that it lies
+between <code>eps.lower</code> and <code>eps.upper</code>.
+</p>
+<p>
+In case <code>eps.lower</code> is specified and <code>eps.upper</code> is missing,
+<code>eps.upper</code> is set to 0.5. In case <code>eps.upper</code> is specified and
+<code>eps.lower</code> is missing, <code>eps.lower</code> is set to 0.
+</p>
+<p>
+If neither <code>eps</code> nor <code>eps.lower</code> and/or <code>eps.upper</code> is
+specified, <code>eps.lower</code> and <code>eps.upper</code> are set to 0 and 0.5,
+respectively.
+</p>
+<p>
+If <code>eps</code> is missing, the radius-minimax estimator in sense of
+Rieder et al. (2001), respectively Section 2.2 of Kohl (2005) is returned.
+</p>
+<p>
+In case of location, respectively scale one additionally has to specify
+<code>sd</code>, respectively <code>mean</code> where <code>sd</code> and <code>mean</code> can
+be a single number, i.e., identical for all rows, respectively columns,
+or a vector, i.e., different for all rows, respectively columns.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+list of location and scale estimates
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>mean </code></td>
+<td>
+(estimated) means </td></tr>
+<tr valign="top"><td><code>sd </code></td>
+<td>
+(estimated) sds </td></tr>
+<tr valign="top"><td><code>contamination interval</code></td>
+<td>
+interval for the amount of gross errors </td></tr>
+<tr valign="top"><td><code>least favorable contamination</code></td>
+<td>
+amount of gross errors used for the computations </td></tr>
+<tr valign="top"><td><code>maximum MSE-inefficiency</code></td>
+<td>
+maximum (asymptotic) MSE-inefficiency </td></tr>
+</table>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing
+the Radius. Statistical Methods and Applications <EM>17</EM>(1) 13-40.
+</p>
+<p>
+Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing
+the Radius. Submitted. Appeared as discussion paper Nr. 81.
+SFB 373 (Quantification and Simulation of Economic Processes),
+Humboldt University, Berlin; also available under
+<a href="www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf">www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf</a>
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a href="roblox.html">roblox</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+ind <- rbinom(200, size=1, prob=0.05)
+X <- matrix(rnorm(200, mean=ind*3, sd=(1-ind) + ind*9), nrow = 2)
+rowRoblox(X)
+rowRoblox(X, k = 3)
+rowRoblox(X, eps = 0.05)
+rowRoblox(X, eps = 0.05, k = 3)
+
+X1 <- t(X)
+colRoblox(X1)
+colRoblox(X1, k = 3)
+colRoblox(X1, eps = 0.05)
+colRoblox(X1, eps = 0.05, k = 3)
+
+X2 <- rbind(rnorm(100, mean = -2, sd = 3), rnorm(100, mean = -1, sd = 4))
+rowRoblox(X2, sd = c(3, 4))
+rowRoblox(X2, eps = 0.03, sd = c(3, 4))
+rowRoblox(X2, sd = c(3, 4), k = 4)
+rowRoblox(X2, eps = 0.03, sd = c(3, 4), k = 4)
+
+X3 <- cbind(rnorm(100, mean = -2, sd = 3), rnorm(100, mean = 1, sd = 2))
+colRoblox(X3, mean = c(-2, 1))
+colRoblox(X3, eps = 0.02, mean = c(-2, 1))
+colRoblox(X3, mean = c(-2, 1), k = 4)
+colRoblox(X3, eps = 0.02, mean = c(-2, 1), k = 4)
+</pre>
+
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
Added: pkg/RobLox/chm/rsOptIC.html
===================================================================
--- pkg/RobLox/chm/rsOptIC.html (rev 0)
+++ pkg/RobLox/chm/rsOptIC.html 2008-02-26 19:26:57 UTC (rev 75)
@@ -0,0 +1,138 @@
+<html><head><title>Computation of the optimally robust IC for AL estimators</title>
+<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+<link rel="stylesheet" type="text/css" href="Rchm.css">
+</head>
+<body>
+
+<table width="100%"><tr><td>rsOptIC(RobLox)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
+<param name="keyword" value="R: rsOptIC">
+<param name="keyword" value=" Computation of the optimally robust IC for AL estimators">
+</object>
+
+
+<h2>Computation of the optimally robust IC for AL estimators</h2>
+
+
+<h3>Description</h3>
+
+<p>
+The function <code>rsOptIC</code> computes the optimally robust IC for
+AL estimators in case of normal scale and (convex) contamination
+neighborhoods. The definition of these estimators can be found
+in Rieder (1994) or Kohl (2005), respectively.
+</p>
+
+
+<h3>Usage</h3>
+
+<pre>
+rsOptIC(r, mean = 0, sd = 1, bUp = 1000, delta = 1e-06, itmax = 100, computeIC = TRUE)
+</pre>
+
+
+<h3>Arguments</h3>
+
+<table summary="R argblock">
+<tr valign="top"><td><code>r</code></td>
+<td>
+non-negative real: neighborhood radius. </td></tr>
+<tr valign="top"><td><code>mean</code></td>
+<td>
+specified mean.</td></tr>
+<tr valign="top"><td><code>sd</code></td>
+<td>
+specified standard deviation.</td></tr>
+<tr valign="top"><td><code>bUp</code></td>
+<td>
+positive real: the upper end point of the
+interval to be searched for the clipping bound b. </td></tr>
+<tr valign="top"><td><code>delta</code></td>
+<td>
+the desired accuracy (convergence tolerance). </td></tr>
+<tr valign="top"><td><code>itmax</code></td>
+<td>
+the maximum number of iterations. </td></tr>
+<tr valign="top"><td><code>computeIC</code></td>
+<td>
+logical: should IC be computed. See details below. </td></tr>
+</table>
+
+<h3>Details</h3>
+
+<p>
+If 'computeIC' is 'FALSE' only the Lagrange multipliers 'A', 'a', and
+'b' contained in the optimally robust IC are computed.
+</p>
+
+
+<h3>Value</h3>
+
+<p>
+If 'computeIC' is 'TRUE' an object of class <code>"ContIC"</code> is returned,
+otherwise a list of Lagrane multipliers
+</p>
+<table summary="R argblock">
+<tr valign="top"><td><code>A</code></td>
+<td>
+standardizing constant </td></tr>
+<tr valign="top"><td><code>a</code></td>
+<td>
+centering constant </td></tr>
+<tr valign="top"><td><code>b</code></td>
+<td>
+optimal clipping bound </td></tr>
+</table>
+
+<h3>Author(s)</h3>
+
+<p>
+Matthias Kohl <a href="mailto:Matthias.Kohl at stamats.de">Matthias.Kohl at stamats.de</a>
+</p>
+
+
+<h3>References</h3>
+
+<p>
+Rieder, H. (1994) <EM>Robust Asymptotic Statistics</EM>. New York: Springer.
+</p>
+<p>
+Kohl, M. (2005) <EM>Numerical Contributions to the Asymptotic Theory of Robustness</EM>.
+Bayreuth: Dissertation.
+</p>
+
+
+<h3>See Also</h3>
+
+<p>
+<code><a onclick="findlink('ROptEst', 'ContIC-class.html')" style="text-decoration: underline; color: blue; cursor: hand">ContIC-class</a></code>, <code><a href="roblox.html">roblox</a></code>
+</p>
+
+
+<h3>Examples</h3>
+
+<pre>
+IC1 <- rsOptIC(r = 0.1)
+distrExOptions("ErelativeTolerance" = 1e-12)
+checkIC(IC1)
+distrExOptions("ErelativeTolerance" = .Machine$double.eps^0.25) # default
+Risks(IC1)
+cent(IC1)
+clip(IC1)
+stand(IC1)
+plot(IC1)
+</pre>
+
+<script Language="JScript">
+function findlink(pkg, fn) {
+var Y, link;
+Y = location.href.lastIndexOf("\\") + 1;
+link = location.href.substring(0, Y);
+link = link + "../../" + pkg + "/chtml/" + pkg + ".chm::/" + fn;
+location.href = link;
+}
+</script>
+
+
+<hr><div align="center">[Package <em>RobLox</em> version 0.6.0 <a href="00Index.html">Index]</a></div>
+
+</body></html>
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