<?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 Øystein Sørensen</title><link>https://osorensen.no/software/</link><description>Recent content in Software on Øystein Sørensen</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 28 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://osorensen.no/software/index.xml" rel="self" type="application/rss+xml"/><item><title>BayesMallowsSMC2: Nested Sequential Monte Carlo for the Bayesian Mallows Model</title><link>https://osorensen.no/software/software6/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software6/</guid><description>This R package provides nested sequential Monte Carlo algorithms for performing sequential inference in the Bayesian Mallows model.</description></item><item><title>galamm - Generalized Additive Latent and Mixed Models</title><link>https://osorensen.no/software/software1/</link><pubDate>Fri, 01 Sep 2023 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software1/</guid><description>This R package contains functions for estimating generalized additive latent and mixed models.</description></item><item><title>BayesianLaterality - Predict Brain Asymmetry Based on Handedness and Dichotic Listening</title><link>https://osorensen.no/software/software4/</link><pubDate>Tue, 01 Sep 2020 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software4/</guid><description>This R package contains functions for estimating whether a subject is left- or right-dominant for language processing based on the results of dichotic listening experiments and information about handedness.</description></item><item><title>metagam: Meta-Analysis of Generalized Additive Models</title><link>https://osorensen.no/software/software5/</link><pubDate>Sat, 01 Feb 2020 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software5/</guid><description>This R package contains functions for meta analysis using generalized additive (mixed) models, by combining fits from multiple studies.</description></item><item><title>BayesMallows: Bayesian Preference Learning with the Mallows Rank Model</title><link>https://osorensen.no/software/software2/</link><pubDate>Mon, 01 Oct 2018 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software2/</guid><description>This R package contains functions for estimating the Bayesian Mallows model in a wide range of situation, using the Metropolis-Hastings algorithm.</description></item><item><title>hdme: High-Dimensional Regression with Measurement Error</title><link>https://osorensen.no/software/software3/</link><pubDate>Thu, 01 Mar 2018 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software3/</guid><description>This R package contains functions for fitting variable selection models in the presence of noise in the predictor variables. In particular, it supports a corrected lasso and the generalized matrix uncertainty selector. In addition, it offers an implementation of the (generalized) Dantzig selector.</description></item></channel></rss>