<?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>whartonstatspassion.r-universe.dev</title><link>https://whartonstatspassion.r-universe.dev</link><description>Recent package updates in whartonstatspassion</description><generator>R-universe</generator><image><url>https://github.com/whartonstatspassion.png</url><title>R packages by whartonstatspassion</title><link>https://whartonstatspassion.r-universe.dev</link></image><lastBuildDate>Tue, 10 Aug 2021 11:51:00 GMT</lastBuildDate><item><title>[elsa-yang98] ConformalSmallest 1.0</title><author>yachong@wharton.upenn.edu (Yachong Yang)</author><description>An implementation of efficiency first conformal prediction
(EFCP) and validity first conformal prediction (VFCP) that
demonstrates both validity (coverage guarantee) and efficiency
(width guarantee). To learn how to use it, check the vignettes
for a quick tutorial. The package is based on the work by Yang
Y., Kuchibhotla A.,(2021) &lt;arxiv:2104.13871&gt;.</description><link>https://github.com/r-universe/elsa-yang98/actions/runs/38035223513</link><pubDate>Tue, 10 Aug 2021 11:51:00 GMT</pubDate><r:package>ConformalSmallest</r:package><r:version>1.0</r:version><r:status>success</r:status><r:repository>https://elsa-yang98.r-universe.dev</r:repository><r:upstream>https://github.com/elsa-yang98/conformalsmallest</r:upstream><r:article><r:source>Example-tuning_free_CQR.Rmd</r:source><r:filename>Example-tuning_free_CQR.html</r:filename><r:title>Example_tuning_free_CQR</r:title><r:created>2021-08-10 11:41:04</r:created><r:modified>2021-08-10 11:41:04</r:modified></r:article><r:article><r:source>Example-tuning_free_ridge_regression.Rmd</r:source><r:filename>Example-tuning_free_ridge_regression.html</r:filename><r:title>Example_tuning_free_ridge_regression</r:title><r:created>2021-08-10 11:41:04</r:created><r:modified>2021-08-10 11:41:04</r:modified></r:article></item></channel></rss>