<?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>esunroc.r-universe.dev</title><link>https://esunroc.r-universe.dev</link><description>Recent package updates in esunroc</description><generator>R-universe</generator><image><url>https://github.com/esunroc.png</url><title>R packages by esunroc</title><link>https://esunroc.r-universe.dev</link></image><lastBuildDate>Fri, 14 Jun 2024 02:44:20 GMT</lastBuildDate><item><title>[esunroc] splmm 1.2.0</title><author>eli_sun@urmc.rochester.edu (Eli Sun)</author><description>Contains functions that fit linear mixed-effects models
for high-dimensional data (p&gt;&gt;n) with penalty for both the
fixed effects and random effects for variable selection. The
details of the algorithm can be found in Luoying Yang PhD
thesis (Yang and Wu 2020). The algorithm implementation is
based on the R package 'lmmlasso'. Reference: Yang L, Wu TT
(2020). Model-Based Clustering of Longitudinal Data in
High-Dimensionality. Unpublished thesis.</description><link>https://github.com/r-universe/esunroc/actions/runs/27400565328</link><pubDate>Fri, 14 Jun 2024 02:44:20 GMT</pubDate><r:package>splmm</r:package><r:version>1.2.0</r:version><r:status>success</r:status><r:repository>https://esunroc.r-universe.dev</r:repository><r:upstream>https://github.com/cran/splmm</r:upstream></item></channel></rss>