<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Software on Abhi Jain</title><link>https://abhijainstats.github.io/software/</link><description>Recent content in Software on Abhi Jain</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://abhijainstats.github.io/software/index.xml" rel="self" type="application/rss+xml"/><item><title>BayesBadger</title><link>https://abhijainstats.github.io/software/bayesbadger/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://abhijainstats.github.io/software/bayesbadger/</guid><description>BayesBadger is an R package for a Bayesian BetA Double GEneralized Regression with mean modeled using individual-level covariates and precision modeled through cluster-level covariates. The model also allows for spatial smoothing through a graph Laplacian prior. A vignette with instructions on how to use the package can be found here and source code can be found on the Github repository.</description></item></channel></rss>