<?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>benrisebrow.r-universe.dev</title><link>https://benrisebrow.r-universe.dev</link><description>Recent package updates in benrisebrow</description><generator>R-universe</generator><image><url>https://github.com/benrisebrow.png</url><title>R packages by benrisebrow</title><link>https://benrisebrow.r-universe.dev</link></image><lastBuildDate>Tue, 17 Feb 2026 09:30:46 GMT</lastBuildDate><item><title>[benrisebrow] LRMiss 0.0.1</title><author>benedict.risebrow@warwick.ac.uk (Benedict Risebrow)</author><description>Provides methods for linear regression in the presence of
missing data, including missingness in covariates and
responses. The package implements two estimators:
'oss_estimator', a low-dimensional semi-supervised method, and
'dantzig_missing', a high-dimensional approach. The tuning
parameter can be selected automatically via
'cv_dantzig_missing'. See the associated methodology paper for
details.</description><link>https://github.com/r-universe/benrisebrow/actions/runs/26275233013</link><pubDate>Tue, 17 Feb 2026 09:30:46 GMT</pubDate><r:package>LRMiss</r:package><r:version>0.0.1</r:version><r:status>success</r:status><r:repository>https://benrisebrow.r-universe.dev</r:repository><r:upstream>https://github.com/benrisebrow/lrmiss</r:upstream></item></channel></rss>