<?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>dwinkler1.r-universe.dev</title><link>https://dwinkler1.r-universe.dev</link><description>Recent package updates in dwinkler1</description><generator>R-universe</generator><image><url>https://github.com/dwinkler1.png</url><title>R packages by dwinkler1</title><link>https://dwinkler1.r-universe.dev</link></image><lastBuildDate>Tue, 24 Mar 2026 07:50:02 GMT</lastBuildDate><item><title>[dwinkler1] shrinkDSM 1.0.2</title><author>daniel.winkler@unsw.edu.au (Daniel Winkler)</author><description>Efficient Markov chain Monte Carlo (MCMC) algorithms for
fully Bayesian estimation of dynamic survival models with
shrinkage priors. Details on the algorithms used are provided
in Wagner (2011) &lt;doi:10.1007/s11222-009-9164-5&gt;, Bitto and
Frühwirth-Schnatter (2019) &lt;doi:10.1016/j.jeconom.2018.11.006&gt;
and Cadonna et al. (2020) &lt;doi:10.3390/econometrics8020020&gt;.</description><link>https://github.com/r-universe/dwinkler1/actions/runs/38878039762</link><pubDate>Tue, 24 Mar 2026 07:50:02 GMT</pubDate><r:package>shrinkDSM</r:package><r:version>1.0.2</r:version><r:status>success</r:status><r:repository>https://dwinkler1.r-universe.dev</r:repository><r:upstream>https://github.com/cran/shrinkDSM</r:upstream></item></channel></rss>