<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Principal Covariates Regression</dc:title>
  <dc:title>R package PCovR version 2.7.2</dc:title>
  <dc:description>Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. &amp; Kiers H. A. L. (1992) &lt;doi:10.1016/0169-7439(92)80100-I&gt;). Several rotation and model selection options are provided.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: GPArotation, ThreeWay, MASS, stats, graphics, Matrix</dc:relation>
  <dc:creator>Kristof Meers &lt;kristof.meers+cran@kuleuven.be&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Marlies Vervloet [aut, cre],
  Henk Kiers [aut],
  Eva Ceulemans [ctb]</dc:contributor>
  <dc:rights>GPL (&gt;= 2)</dc:rights>
  <dc:date>2023-10-26</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=PCovR</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.PCovR</dc:identifier>
</oai_dc:dc>