<?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>tonycanale.r-universe.dev</title><link>https://tonycanale.r-universe.dev</link><description>Recent package updates in tonycanale</description><generator>R-universe</generator><image><url>https://github.com/tonycanale.png</url><title>R packages by tonycanale</title><link>https://tonycanale.r-universe.dev</link></image><lastBuildDate>Thu, 29 Oct 2026 11:50:35 GMT</lastBuildDate><item><title>[tonycanale] glt 1.0</title><author>antonio.canale@unipd.it (Antonio Canale)</author><description>Sparse Bayesian factor models for multivariate data, built
around a flexible Generalized Lower Triangular (GLT) process
prior on the loading matrix by Canale and Frühwirth-Schnatter
(2026) &lt;doi:10.48550/arXiv.2610.09762&gt;. The number of active
factors, their sparsity pattern, and the loadings themselves
are learned jointly via a Markov chain Monte Carlo sampler
implemented in C++ with 'Rcpp' and 'RcppArmadillo'.</description><link>https://github.com/r-universe/tonycanale/actions/runs/41146097260</link><pubDate>Thu, 29 Oct 2026 11:50:35 GMT</pubDate><r:package>glt</r:package><r:version>1.0</r:version><r:status>success</r:status><r:repository>https://tonycanale.r-universe.dev</r:repository><r:upstream>https://github.com/tonycanale/glt</r:upstream></item><item><title>[tonycanale] rmp 2.2</title><author>antonio.canale@unipd.it (Antonio Canale)</author><description>Performs univariate probability mass function estimation
via Bayesian nonparametric mixtures of rounded kernels as in
Canale and Dunson (2011) &lt;doi:10.1198/jasa.2011.tm10552&gt;.</description><link>https://github.com/r-universe/tonycanale/actions/runs/37439096265</link><pubDate>Thu, 14 Dec 2023 02:39:13 GMT</pubDate><r:package>rmp</r:package><r:version>2.2</r:version><r:status>success</r:status><r:repository>https://tonycanale.r-universe.dev</r:repository><r:upstream>https://github.com/cran/rmp</r:upstream></item><item><title>[tonycanale] CoMiRe 0.8</title><author>antonio.canale@unipd.it (Antonio Canale)</author><description>Posterior inference under the convex mixture regression
(CoMiRe) models introduced by Canale, Durante, and Dunson
(2018) &lt;doi:10.1111/biom.12917&gt;.</description><link>https://github.com/r-universe/tonycanale/actions/runs/38070194469</link><pubDate>Wed, 23 Aug 2023 10:31:04 GMT</pubDate><r:package>CoMiRe</r:package><r:version>0.8</r:version><r:status>success</r:status><r:repository>https://tonycanale.r-universe.dev</r:repository><r:upstream>https://github.com/cran/CoMiRe</r:upstream></item></channel></rss>