<?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>cehi-code-repos.r-universe.dev</title><link>https://cehi-code-repos.r-universe.dev</link><description>Recent package updates in cehi-code-repos</description><generator>R-universe</generator><image><url>https://github.com/cehi-code-repos.png</url><title>R packages by cehi-code-repos</title><link>https://cehi-code-repos.r-universe.dev</link></image><lastBuildDate>Thu, 14 May 2026 22:49:05 GMT</lastBuildDate><item><title>[cehi-code-repos] RSTr 1.1.4</title><author>sfq1@cdc.gov (David DeLara)</author><description>Takes Poisson or Binomial discrete spatial data and runs a
Gibbs sampler for a variety of Spatiotemporal Conditional
Autoregressive (CAR) models. Includes measures to prevent
estimate over-smoothing through a restriction of model
informativeness for select models. Also provides tools to load
output and get median estimates. Implements methods from Besag,
York, and Mollié (1991) &quot;Bayesian image restoration, with two
applications in spatial statistics&quot; &lt;doi:10.1007/BF00116466&gt;,
Gelfand and Vounatsou (2003) &quot;Proper multivariate conditional
autoregressive models for spatial data analysis&quot;
&lt;doi:10.1093/biostatistics/4.1.11&gt;, Quick et al. (2017)
&quot;Multivariate spatiotemporal modeling of age-specific stroke
mortality&quot; &lt;doi:10.1214/17-AOAS1068&gt;, and Quick et al. (2021)
&quot;Evaluating the informativeness of the Besag-York-Mollié CAR
model&quot; &lt;doi:10.1016/j.sste.2021.100420&gt;.</description><link>https://github.com/r-universe/cehi-code-repos/actions/runs/27459889032</link><pubDate>Thu, 14 May 2026 22:49:05 GMT</pubDate><r:package>RSTr</r:package><r:version>1.1.4</r:version><r:status>failure</r:status><r:repository>https://cehi-code-repos.r-universe.dev</r:repository><r:upstream>https://github.com/CEHI-code-repos/RSTr</r:upstream></item></channel></rss>