<?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>ifoa-adswp.r-universe.dev</title><link>https://ifoa-adswp.r-universe.dev</link><description>Recent package updates in ifoa-adswp</description><generator>R-universe</generator><image><url>https://github.com/ifoa-adswp.png</url><title>R packages by ifoa-adswp</title><link>https://ifoa-adswp.r-universe.dev</link></image><lastBuildDate>Sat, 23 May 2026 17:36:34 GMT</lastBuildDate><item><title>[ifoa-adswp] IBLM 2.0.1</title><author>karol.gawlowski@citystgeorges.ac.uk (Karol Gawlowski)</author><description>Implements Interpretable Boosted Linear Models (IBLMs).
These combine a conventional generalized linear model (GLM)
with a machine learning component, such as XGBoost. The package
also provides tools within for explaining and analyzing these
models. For more details see Gawlowski and Wang (2025)
&lt;https://ifoa-adswp.github.io/IBLM/reference/figures/iblm_paper.pdf&gt;.</description><link>https://github.com/r-universe/ifoa-adswp/actions/runs/27949231331</link><pubDate>Sat, 23 May 2026 17:36:34 GMT</pubDate><r:package>IBLM</r:package><r:version>2.0.1</r:version><r:status>success</r:status><r:repository>https://ifoa-adswp.r-universe.dev</r:repository><r:upstream>https://github.com/ifoa-adswp/iblm</r:upstream><r:article><r:source>IBLM.Rmd</r:source><r:filename>IBLM.html</r:filename><r:title>IBLM</r:title><r:created>2025-11-23 10:24:12</r:created><r:modified>2026-05-18 20:37:21</r:modified></r:article></item></channel></rss>