<?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>wencanhong-coder.r-universe.dev</title><link>https://wencanhong-coder.r-universe.dev</link><description>Recent package updates in wencanhong-coder</description><generator>R-universe</generator><image><url>https://github.com/wencanhong-coder.png</url><title>R packages by wencanhong-coder</title><link>https://wencanhong-coder.r-universe.dev</link></image><lastBuildDate>Fri, 12 Jan 2024 02:39:48 GMT</lastBuildDate><item><title>[wencanhong-coder] BeSS 2.0.4</title><author>wencanhong@gmail.com (Canhong Wen)</author><description>An implementation of best subset selection in generalized
linear model and Cox proportional hazard model via the primal
dual active set algorithm proposed by Wen, C., Zhang, A., Quan,
S. and Wang, X. (2020) &lt;doi:10.18637/jss.v094.i04&gt;. The
algorithm formulates coefficient parameters and residuals as
primal and dual variables and utilizes efficient active set
selection strategies based on the complementarity of the primal
and dual variables.</description><link>https://github.com/r-universe/wencanhong-coder/actions/runs/35326804326</link><pubDate>Fri, 12 Jan 2024 02:39:48 GMT</pubDate><r:package>BeSS</r:package><r:version>2.0.4</r:version><r:status>success</r:status><r:repository>https://wencanhong-coder.r-universe.dev</r:repository><r:upstream>https://github.com/cran/BeSS</r:upstream></item><item><title>[wencanhong-coder] glmlep 0.2</title><author>wencanhong@gmail.com (Canhong Wen)</author><description>Efficient algorithms for fitting regularization paths for
linear or logistic regression models penalized by LEP.</description><link>https://github.com/r-universe/wencanhong-coder/actions/runs/35326809068</link><pubDate>Fri, 08 Mar 2019 14:10:10 GMT</pubDate><r:package>glmlep</r:package><r:version>0.2</r:version><r:status>success</r:status><r:repository>https://wencanhong-coder.r-universe.dev</r:repository><r:upstream>https://github.com/cran/glmlep</r:upstream></item></channel></rss>