<?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>Clustered Random Forests for Optimal Prediction and Inference of
Clustered Data</dc:title>
  <dc:title>R package corrRF version 1.1.0</dc:title>
  <dc:description>A clustered random forest algorithm for fitting random forests for data of independent clusters, that exhibit within cluster dependence. 
    Details of the method can be found in Young and Buehlmann (2025) &lt;doi:10.48550/arXiv.2503.12634&gt;. </dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.2.0)</dc:relation>
  <dc:relation>Imports: Rcpp, rpart</dc:relation>
  <dc:relation>LinkingTo: Rcpp</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown, testthat</dc:relation>
  <dc:creator>Elliot H. Young &lt;ey244@cam.ac.uk&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Elliot H. Young [aut, cre]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2025-03-20</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=corrRF</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.corrRF</dc:identifier>
</oai_dc:dc>
