<?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>awqx.r-universe.dev</title><link>https://awqx.r-universe.dev</link><description>Recent package updates in awqx</description><generator>R-universe</generator><image><url>https://github.com/awqx.png</url><title>R packages by awqx</title><link>https://awqx.r-universe.dev</link></image><lastBuildDate>Mon, 18 May 2026 23:11:54 GMT</lastBuildDate><item><title>[awqx] fastFMM 1.0.1.9000</title><author>axin@andrew.cmu.edu (Al Xin)</author><description>Implementation of the fast univariate inference approach
(Cui et al. (2022) &lt;doi:10.1080/10618600.2021.1950006&gt;,
Loewinger et al. (2024) &lt;doi:10.7554/eLife.95802.2&gt;, Xin et al.
(2025) &lt;doi:10.7554/eLife.109428.1&gt;) for fitting functional
mixed models. User guides and Python package information can be
found at &lt;https://github.com/gloewing/photometry_FLMM&gt;.</description><link>https://github.com/r-universe/awqx/actions/runs/26084625109</link><pubDate>Mon, 18 May 2026 23:11:54 GMT</pubDate><r:package>fastFMM</r:package><r:version>1.0.1.9000</r:version><r:status>success</r:status><r:repository>https://awqx.r-universe.dev</r:repository><r:upstream>https://github.com/awqx/fastfmm</r:upstream><r:article><r:source>fastFMM.Rmd</r:source><r:filename>fastFMM.html</r:filename><r:title>Introduction to fastFMM model fitting</r:title><r:created>2025-07-22 21:01:17</r:created><r:modified>2026-05-18 00:28:53</r:modified></r:article><r:article><r:source>d2pvt.Rmd</r:source><r:filename>d2pvt.html</r:filename><r:title>Example fastFMM application to variable trial lengths</r:title><r:created>2025-08-15 20:17:33</r:created><r:modified>2026-05-18 00:28:53</r:modified></r:article></item></channel></rss>