<?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>cberrettstat.r-universe.dev</title><link>https://cberrettstat.r-universe.dev</link><description>Recent package updates in cberrettstat</description><generator>R-universe</generator><image><url>https://github.com/cberrettstat.png</url><title>R packages by cberrettstat</title><link>https://cberrettstat.r-universe.dev</link></image><lastBuildDate>Wed, 13 May 2026 15:33:30 GMT</lastBuildDate><item><title>[cberrettstat] BSTFA 0.1.1</title><author>cberrett@stat.byu.edu (Candace Berrett)</author><description>Implements Bayesian spatio-temporal factor analysis models
for multivariate data observed across space and time. The
package provides tools for model fitting via Markov chain Monte
Carlo (MCMC), spatial and temporal interpolation, and
visualization of latent factors and loadings to support
inference and exploration of underlying spatio-temporal
patterns. Designed for use in environmental, ecological, or
public health applications, with support for posterior
prediction and uncertainty quantification. Includes functions
such as BSTFA() for model fitting and plot_factor() to
visualize the latent processes.  Functions are based on and
extended from methods described in Berrett, et al. (2020)
&lt;doi:10.1002/env.2609&gt;.</description><link>https://github.com/r-universe/cberrettstat/actions/runs/27398726366</link><pubDate>Wed, 13 May 2026 15:33:30 GMT</pubDate><r:package>BSTFA</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://cberrettstat.r-universe.dev</r:repository><r:upstream>https://github.com/cberrettstat/bstfa</r:upstream><r:article><r:source>BSTFA-Vignette.Rmd</r:source><r:filename>BSTFA-Vignette.html</r:filename><r:title>BSTFA Package</r:title><r:created>2025-05-22 18:45:09</r:created><r:modified>2025-07-30 18:50:41</r:modified></r:article></item></channel></rss>