<?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>tennenbaumj.r-universe.dev</title><link>https://tennenbaumj.r-universe.dev</link><description>Recent package updates in tennenbaumj</description><generator>R-universe</generator><image><url>https://github.com/tennenbaumj.png</url><title>R packages by tennenbaumj</title><link>https://tennenbaumj.r-universe.dev</link></image><lastBuildDate>Tue, 03 Mar 2026 04:34:05 GMT</lastBuildDate><item><title>[tennenbaumj] bclogit 1.1.1</title><author>kapelner@qc.cuny.edu (Adam Kapelner)</author><description>Performs inference for Bayesian conditional logistic
regression with informative priors built from the concordant
pair data. We include many options to build the priors. And we
include many options during the inference step for estimation,
testing and confidence set creation. For details, see Kapelner
and Tennenbaum (2026) &quot;Improved Conditional Logistic Regression
using Information in Concordant Pairs with Software&quot;
&lt;doi:10.48550/arXiv.2602.08212&gt;.</description><link>https://github.com/r-universe/tennenbaumj/actions/runs/28006060254</link><pubDate>Tue, 03 Mar 2026 04:34:05 GMT</pubDate><r:package>bclogit</r:package><r:version>1.1.1</r:version><r:status>success</r:status><r:repository>https://tennenbaumj.r-universe.dev</r:repository><r:upstream>https://github.com/tennenbaumj/bclogit_package_and_paper_repo</r:upstream></item></channel></rss>