<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>dschindler.r-universe.dev</title><link>https://dschindler.r-universe.dev</link><description>Recent package updates in dschindler</description><generator>R-universe</generator><image><url>https://github.com/dschindler.png</url><title>R packages by dschindler</title><link>https://dschindler.r-universe.dev</link></image><lastBuildDate>Thu, 01 Jun 2023 11:50:07 GMT</lastBuildDate><item><title>[dschindler] intrinsicKappa 0.1</title><author>dv.schindler@gmail.com (David Schindler)</author><description>Kappa statistics is one of the most used methods to
evaluate the effectiveness of inpsections based on attribute
assessments in industry. However, its estimation by available
methods does not provide its &quot;real&quot; or &quot;intrinstic&quot; value. This
package provides functions for the computation of the intrinsic
kappa value as it is described in: Rafael Sanchez-Marquez,
Frank Gerhorst and David Schindler (2023) &quot;Effectiveness of
quality inspections of attributive characteristics – A novel
and practical method for estimating the “intrinsic” value of
kappa based on alpha and beta statistics.&quot;
&lt;doi:10.1016/j.cie.2023.109006&gt;.</description><link>https://github.com/r-universe/dschindler/actions/runs/37192071839</link><pubDate>Thu, 01 Jun 2023 11:50:07 GMT</pubDate><r:package>intrinsicKappa</r:package><r:version>0.1</r:version><r:status>success</r:status><r:repository>https://dschindler.r-universe.dev</r:repository><r:upstream>https://github.com/cran/intrinsicKappa</r:upstream><r:article><r:source>intrinsicKappa.Rmd</r:source><r:filename>intrinsicKappa.html</r:filename><r:title>Get started with intrinsicKappa</r:title><r:created>2023-06-01 11:50:07</r:created><r:modified>2023-06-01 11:50:07</r:modified></r:article></item><item><title>[dschindler] unitedR 0.4</title><author>dv.schindler@gmail.com (David Schindler)</author><description>United is a software tool which can be downloaded at the
following website
&lt;http://www.schroepl.net/pbm/software/united/&gt;. In general, it
is a virtual manager game for football teams. This package
contains helpful functions for determining an optimal formation
for a virtual match in United. E.g. knowing that the opponent
has a strong defensive it is advisable to beat him in the
midfield. Furthermore, this package contains functions for
computing the optimal usage of hardness in a game.</description><link>https://github.com/r-universe/dschindler/actions/runs/38721541613</link><pubDate>Tue, 23 Jun 2020 14:40:02 GMT</pubDate><r:package>unitedR</r:package><r:version>0.4</r:version><r:status>success</r:status><r:repository>https://dschindler.r-universe.dev</r:repository><r:upstream>https://github.com/cran/unitedR</r:upstream><r:article><r:source>unitedR.Rnw</r:source><r:filename>unitedR.pdf</r:filename><r:title>unitedR</r:title><r:created>2015-10-13 17:42:09</r:created><r:modified>2018-01-05 11:39:45</r:modified></r:article></item></channel></rss>