<?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>timktsang.r-universe.dev</title><link>https://timktsang.r-universe.dev</link><description>Recent package updates in timktsang</description><generator>R-universe</generator><image><url>https://github.com/timktsang.png</url><title>R packages by timktsang</title><link>https://timktsang.r-universe.dev</link></image><lastBuildDate>Wed, 08 Apr 2026 22:51:39 GMT</lastBuildDate><item><title>[timktsang] hhdynamics 1.3.3</title><author>timkltsang@gmail.com (Tim Tsang)</author><description>A Bayesian household transmission model to estimate
household transmission dynamics, with accounting for infection
from community and tertiary cases.</description><link>https://github.com/r-universe/timktsang/actions/runs/27085238567</link><pubDate>Wed, 08 Apr 2026 22:51:39 GMT</pubDate><r:package>hhdynamics</r:package><r:version>1.3.3</r:version><r:status>success</r:status><r:repository>https://timktsang.r-universe.dev</r:repository><r:upstream>https://github.com/timktsang/hhdynamics</r:upstream><r:article><r:source>hhdynamics-intro.Rmd</r:source><r:filename>hhdynamics-intro.html</r:filename><r:title>Getting Started with hhdynamics</r:title><r:created>2026-03-19 08:52:55</r:created><r:modified>2026-03-23 05:23:54</r:modified></r:article><r:article><r:source>hhdynamics-methodology.Rmd</r:source><r:filename>hhdynamics-methodology.html</r:filename><r:title>Statistical Methodology</r:title><r:created>2026-03-23 05:23:54</r:created><r:modified>2026-03-23 05:23:54</r:modified></r:article></item><item><title>[timktsang] seroreconstruct 1.1.5</title><author>timkltsang@gmail.com (Tim Tsang)</author><description>A Bayesian framework for inferring influenza infection
status from serial antibody measurements. Jointly estimates
season-specific infection probabilities, antibody boosting and
waning after infection, and baseline hemagglutination
inhibition (HAI) titer distributions via Markov chain Monte
Carlo (MCMC). Supports multi-season analysis and subgroup
comparisons via a group_by interface. See Tsang et al. (2022)
&lt;doi:10.1038/s41467-022-29310-8&gt; for methodological details.</description><link>https://github.com/r-universe/timktsang/actions/runs/26876881847</link><pubDate>Mon, 30 Mar 2026 14:58:43 GMT</pubDate><r:package>seroreconstruct</r:package><r:version>1.1.5</r:version><r:status>success</r:status><r:repository>https://timktsang.r-universe.dev</r:repository><r:upstream>https://github.com/timktsang/seroreconstruct</r:upstream><r:article><r:source>introduction.Rmd</r:source><r:filename>introduction.html</r:filename><r:title>Getting Started with seroreconstruct</r:title><r:created>2026-03-23 08:05:26</r:created><r:modified>2026-03-30 14:22:23</r:modified></r:article><r:article><r:source>methodology.Rmd</r:source><r:filename>methodology.html</r:filename><r:title>Statistical Methodology</r:title><r:created>2026-03-23 08:05:26</r:created><r:modified>2026-03-23 08:56:06</r:modified></r:article></item></channel></rss>