<?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>tl2624.r-universe.dev</title><link>https://tl2624.r-universe.dev</link><description>Recent package updates in tl2624</description><generator>R-universe</generator><image><url>https://github.com/tl2624.png</url><title>R packages by tl2624</title><link>https://tl2624.r-universe.dev</link></image><lastBuildDate>Thu, 22 May 2025 18:42:00 GMT</lastBuildDate><item><title>[tl2624] apm 0.1.1</title><author>thomas.leavitt@baruch.cuny.edu (Thomas Leavitt)</author><description>In panel data settings, specifies set of candidate models,
fits them to data from pre-treatment validation periods, and
selects model as average over candidate models, weighting each
by posterior probability of being most robust given its
differential average prediction errors in pre-treatment
validation periods. Subsequent estimation and inference of
causal effect's bounds accounts for both model and sampling
uncertainty, and calculates the robustness changepoint value at
which bounds go from excluding to including 0. The package also
includes a range of diagnostic plots, such as those
illustrating models' differential average prediction errors and
the posterior distribution of which model is most robust.</description><link>https://github.com/r-universe/tl2624/actions/runs/26020786925</link><pubDate>Thu, 22 May 2025 18:42:00 GMT</pubDate><r:package>apm</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://tl2624.r-universe.dev</r:repository><r:upstream>https://github.com/tl2624/apm</r:upstream><r:article><r:source>apm.Rmd</r:source><r:filename>apm.html</r:filename><r:title>Introduction to the apm Package</r:title><r:created>2025-02-26 19:58:21</r:created><r:modified>2025-05-22 18:42:00</r:modified></r:article></item></channel></rss>