<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Matrix Uncertainty Selector on Øystein Sørensen</title><link>https://osorensen.no/tags/matrix-uncertainty-selector/</link><description>Recent content in Matrix Uncertainty Selector on Øystein Sørensen</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 08 May 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://osorensen.no/tags/matrix-uncertainty-selector/index.xml" rel="self" type="application/rss+xml"/><item><title>hdme: High-Dimensional Regression with Measurement Error</title><link>https://osorensen.no/software/software3/</link><pubDate>Thu, 01 Mar 2018 00:00:00 +0000</pubDate><guid>https://osorensen.no/software/software3/</guid><description>This R package contains functions for fitting variable selection models in the presence of noise in the predictor variables. In particular, it supports a corrected lasso and the generalized matrix uncertainty selector. In addition, it offers an implementation of the (generalized) Dantzig selector.</description></item></channel></rss>