<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>NUTS on Øystein Sørensen</title><link>https://osorensen.no/tags/nuts/</link><description>Recent content in NUTS on Øystein Sørensen</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 25 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://osorensen.no/tags/nuts/index.xml" rel="self" type="application/rss+xml"/><item><title>A Hybrid NUTS-Gibbs Sampler with State Space Marginalization for Estimation of Dynamic Structural Equation Models with Binomial Outcomes</title><link>https://osorensen.no/papers/paper16/</link><pubDate>Wed, 25 Mar 2026 00:00:00 +0000</pubDate><guid>https://osorensen.no/papers/paper16/</guid><description>This paper presents a hybrid sampler &amp;ndash; alternating between one step of the No-U-Turn Sampler (NUTS) and one Gibbs step &amp;ndash; for estimating dynamic structural equation models with binomial outcomes. The Gibbs step handles Pólya-Gamma distributed latent variables arising from a logit link, and the NUTS step uses a Kalman filter to marginalize over latent states. We demonstrate that the proposed sampler makes DSEM estimation with binomial data feasible for larger data and models than previously possible. arXiv preprint.</description></item></channel></rss>