<?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>yuzh98.r-universe.dev</title><link>https://yuzh98.r-universe.dev</link><description>Recent package updates in yuzh98</description><generator>R-universe</generator><image><url>https://github.com/yuzh98.png</url><title>R packages by yuzh98</title><link>https://yuzh98.r-universe.dev</link></image><lastBuildDate>Fri, 14 Aug 2026 10:48:59 GMT</lastBuildDate><item><title>[yuzh98] combreg 0.2.0</title><author>hugh.stats@gmail.com (Hugh Zheng)</author><description>Bayesian regression whose response data are integer-valued
vectors subject to combinatorial constraints in the form of
Ay&lt;=b. Implements the Metropolis-Hastings-within-Gibbs sampler
of Zheng et al. (2026) &lt;doi:10.1080/01621459.2026.2714575&gt;, an
unconstrained probit baseline for comparison, benchmarking
helpers, MCMC and regression diagnostics (effective sample
sizes, split-Rhat, structured reports), plotting methods
(trace, autocorrelation, violin, effective-sample-size,
sampling-efficiency, residual heat map), and utilities for
constraint validation (total unimodularity, feasibility) and
data simulation.</description><link>https://github.com/r-universe/yuzh98/actions/runs/38385654770</link><pubDate>Fri, 14 Aug 2026 10:48:59 GMT</pubDate><r:package>combreg</r:package><r:version>0.2.0</r:version><r:status>success</r:status><r:repository>https://yuzh98.r-universe.dev</r:repository><r:upstream>https://github.com/yuzh98/combreg</r:upstream><r:article><r:source>diagnostics.Rmd</r:source><r:filename>diagnostics.html</r:filename><r:title>Diagnostics and benchmarking</r:title><r:created>2026-07-12 18:35:34</r:created><r:modified>2026-07-20 19:31:22</r:modified></r:article><r:article><r:source>combreg.Rmd</r:source><r:filename>combreg.html</r:filename><r:title>Introduction to combreg</r:title><r:created>2026-07-12 05:27:14</r:created><r:modified>2026-07-20 19:31:22</r:modified></r:article></item></channel></rss>