<?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>analopezcheda.r-universe.dev</title><link>https://analopezcheda.r-universe.dev</link><description>Recent package updates in analopezcheda</description><generator>R-universe</generator><image><url>https://github.com/analopezcheda.png</url><title>R packages by analopezcheda</title><link>https://analopezcheda.r-universe.dev</link></image><lastBuildDate>Sat, 19 Aug 2023 11:30:35 GMT</lastBuildDate><item><title>[analopezcheda] PLRModels 1.4</title><author>ana.lopez.cheda@udc.es (Ana Lopez-Cheda)</author><description>Contains statistical inference tools applied to Partial
Linear Regression (PLR) models. Specifically, point estimation,
confidence intervals estimation, bandwidth selection,
goodness-of-fit tests and analysis of covariance are
considered. Kernel-based methods, combined with ordinary least
squares estimation, are used and time series errors are
allowed. In addition, these techniques are also implemented for
both parametric (linear) and nonparametric regression models.</description><link>https://github.com/r-universe/analopezcheda/actions/runs/37929606517</link><pubDate>Sat, 19 Aug 2023 11:30:35 GMT</pubDate><r:package>PLRModels</r:package><r:version>1.4</r:version><r:status>success</r:status><r:repository>https://analopezcheda.r-universe.dev</r:repository><r:upstream>https://github.com/cran/PLRModels</r:upstream></item></channel></rss>