<?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>jessica306a.r-universe.dev</title><link>https://jessica306a.r-universe.dev</link><description>Recent package updates in jessica306a</description><generator>R-universe</generator><image><url>https://github.com/jessica306a.png</url><title>R packages by jessica306a</title><link>https://jessica306a.r-universe.dev</link></image><lastBuildDate>Tue, 19 Aug 2025 13:20:02 GMT</lastBuildDate><item><title>[jessica306a] PAGE 0.4.0</title><author>jessica306a@gmail.com (Wan-Yi Chang)</author><description>We consider the network structure detection for variables
Y with auxiliary variables X accommodated, which are possibly
subject to measurement error. The following three functions are
designed to address various structures by different methods :
one is NP_Graph() that is used for handling the nonlinear
relationship between the responses and the covariates, another
is Joint_Gaussian() that is used for correction in linear
regression models via the Gaussian maximum likelihood, and the
other Cond_Gaussian() is for linear regression models via
conditional likelihood function.</description><link>https://github.com/r-universe/jessica306a/actions/runs/25957613830</link><pubDate>Tue, 19 Aug 2025 13:20:02 GMT</pubDate><r:package>PAGE</r:package><r:version>0.4.0</r:version><r:status>success</r:status><r:repository>https://jessica306a.r-universe.dev</r:repository><r:upstream>https://github.com/cran/PAGE</r:upstream></item></channel></rss>