<?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>wan-ting-jin.r-universe.dev</title><link>https://wan-ting-jin.r-universe.dev</link><description>Recent package updates in wan-ting-jin</description><generator>R-universe</generator><image><url>https://github.com/wan-ting-jin.png</url><title>R packages by wan-ting-jin</title><link>https://wan-ting-jin.r-universe.dev</link></image><lastBuildDate>Sat, 01 Aug 2026 02:50:02 GMT</lastBuildDate><item><title>[wan-ting-jin] multiModTest 1.1</title><author>jinwanting5@gmail.com (Wanting Jin)</author><description>Provides methods for quantifying the information gain
contributed by individual modalities in multimodal regression
models. Information gain is measured using Expected Relative
Entropy (ERE) or pseudo-R² metrics, with corresponding
confidence intervals. Currently supports linear regression,
logistic regression, and the Cox proportional hazards model. A
robust Median-of-Means based estimator is also provided for
heavy-tailed responses under the Gaussian and Negative-Binomial
families, with basic bootstrap confidence intervals.</description><link>https://github.com/r-universe/wan-ting-jin/actions/runs/38542216694</link><pubDate>Sat, 01 Aug 2026 02:50:02 GMT</pubDate><r:package>multiModTest</r:package><r:version>1.1</r:version><r:status>success</r:status><r:repository>https://wan-ting-jin.r-universe.dev</r:repository><r:upstream>https://github.com/cran/multiModTest</r:upstream></item></channel></rss>