<?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>mastatlab.r-universe.dev</title><link>https://mastatlab.r-universe.dev</link><description>Recent package updates in mastatlab</description><generator>R-universe</generator><image><url>https://github.com/mastatlab.png</url><title>R packages by mastatlab</title><link>https://mastatlab.r-universe.dev</link></image><lastBuildDate>Wed, 22 Jul 2026 23:56:02 GMT</lastBuildDate><item><title>[mastatlab] PTT 1.0.1</title><author>mastatlab@gmail.com (Li Ma)</author><description>Fits Bayesian nonparametric models based on Pólya tree
processes, including adaptive Pólya trees, Markov adaptive
Pólya trees, optional Pólya trees, and their
conditional-density counterparts. Methods are described in Ma
(2017) &lt;doi:10.1214/16-BA1021&gt;, Ma (2017)
&lt;doi:10.1214/17-EJS1254&gt;, and Wong and Ma (2010)
&lt;doi:10.1214/09-AOS755&gt;.</description><link>https://github.com/r-universe/mastatlab/actions/runs/29985649849</link><pubDate>Wed, 22 Jul 2026 23:56:02 GMT</pubDate><r:package>PTT</r:package><r:version>1.0.1</r:version><r:status>success</r:status><r:repository>https://mastatlab.r-universe.dev</r:repository><r:upstream>https://github.com/mastatlab/ptt</r:upstream></item><item><title>[mastatlab] MRS 1.3.2</title><author>mastatlab@gmail.com (Li Ma)</author><description>Implements the multi-resolution scanning (MRS) method for
cross-sample distribution comparisons, as described in Soriano
and Ma (2017) &lt;doi:10.1111/rssb.12180&gt;, and the analysis of
distributional variation (ANDOVA) method for cross-group
comparisons introduced in Ma and Soriano (2018)
&lt;doi:10.1080/10618600.2017.1402774&gt;. Both methods use
nonparametric models on multi-resolution partition trees to
detect and characterize differences among distributions, with
tools for visualizing the results.</description><link>https://github.com/r-universe/mastatlab/actions/runs/29985648499</link><pubDate>Wed, 22 Jul 2026 09:03:56 GMT</pubDate><r:package>MRS</r:package><r:version>1.3.2</r:version><r:status>success</r:status><r:repository>https://mastatlab.r-universe.dev</r:repository><r:upstream>https://github.com/mastatlab/mrs</r:upstream></item><item><title>[mastatlab] FES 1.0</title><author>mastatlab@gmail.com (Li Ma)</author><description>Implements Fisher exact scanning (FES), a multiscale test
of dependence for continuous or discrete bivariate data. The
method scans nested binary partitions using Fisher's exact
tests and combines evidence across windows and resolutions with
Sidak, Bonferroni, and meta-analysis corrections. The
methodology is described in Ma and Mao (2019)
&lt;doi:10.1080/01621459.2017.1397522&gt;.</description><link>https://github.com/r-universe/mastatlab/actions/runs/29985646375</link><pubDate>Tue, 14 Jul 2026 12:28:38 GMT</pubDate><r:package>FES</r:package><r:version>1.0</r:version><r:status>success</r:status><r:repository>https://mastatlab.r-universe.dev</r:repository><r:upstream>https://github.com/mastatlab/fes</r:upstream></item></channel></rss>