<?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>alonkipnis.r-universe.dev</title><link>https://alonkipnis.r-universe.dev</link><description>Recent package updates in alonkipnis</description><generator>R-universe</generator><image><url>https://github.com/alonkipnis.png</url><title>R packages by alonkipnis</title><link>https://alonkipnis.r-universe.dev</link></image><lastBuildDate>Wed, 21 Oct 2026 17:20:02 GMT</lastBuildDate><item><title>[alonkipnis] survHC 0.1.0</title><author>alonkipnis@gmail.com (Alon Kipnis)</author><description>Implements omnibus tests for comparing two right-censored
survival samples that are powerful against sparse departures
from equal hazards, where the hazard difference is concentrated
in a small and a priori unknown subset of the follow-up. Exact
hypergeometric p-values are computed for each time interval and
aggregated with the Higher Criticism statistic of Donoho and
Jin (2004) &lt;doi:10.1214/009053604000000265&gt;, or alternatively
with the Berk-Jones, Fisher or minimum-p statistics. Global
p-values are obtained by permuting group labels, and the
intervals driving a detection can be recovered for diagnostic
plotting. Tests accept either two samples as vectors or the
usual survival formula. The method is described in Kipnis,
Galili and Yakhini (2026) &lt;doi:10.1093/biomet/asaf075&gt;, and the
companion application note is Kipnis, Galili and Yakhini (2026)
&lt;doi:10.48550/arXiv.2610.07268&gt;.</description><link>https://github.com/r-universe/alonkipnis/actions/runs/39760470701</link><pubDate>Wed, 21 Oct 2026 17:20:02 GMT</pubDate><r:package>survHC</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://alonkipnis.r-universe.dev</r:repository><r:upstream>https://github.com/cran/survHC</r:upstream></item></channel></rss>