<?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>chongliang-luo.r-universe.dev</title><link>https://chongliang-luo.r-universe.dev</link><description>Recent package updates in chongliang-luo</description><generator>R-universe</generator><image><url>https://github.com/chongliang-luo.png</url><title>R packages by chongliang-luo</title><link>https://chongliang-luo.r-universe.dev</link></image><lastBuildDate>Mon, 17 Nov 2025 21:50:52 GMT</lastBuildDate><item><title>[chongliang-luo] pda 1.3.0</title><author>luocl3009@gmail.com (Chongliang Luo)</author><description>A collection of privacy-preserving distributed algorithms
(PDAs) for conducting federated statistical learning across
multiple data sites. The PDA framework includes models for
various tasks such as regression, trial emulation, causal
inference, design-specific analysis, and clustering. The PDA
algorithms run on a lead site and only require summary
statistics from collaborating sites, with one or few
iterations. The package can be used together with the online
data transfer system (&lt;https://pda-ota.pdamethods.org/&gt;) for
safe and convenient collaboration. For more information, please
visit our software websites: &lt;https://github.com/Penncil/pda&gt;,
and &lt;https://pdamethods.org/&gt;.</description><link>https://github.com/r-universe/chongliang-luo/actions/runs/29480143600</link><pubDate>Mon, 17 Nov 2025 21:50:52 GMT</pubDate><r:package>pda</r:package><r:version>1.3.0</r:version><r:status>success</r:status><r:repository>https://chongliang-luo.r-universe.dev</r:repository><r:upstream>https://github.com/cran/pda</r:upstream></item></channel></rss>