corrRF: Clustered Random Forests for Optimal Prediction and Inference of Clustered Data

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) <doi:10.48550/arXiv.2503.12634>.

Version: 1.1.0
Depends: R (≥ 4.2.0)
Imports: Rcpp, rpart
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat
Published: 2025-03-20
DOI: 10.32614/CRAN.package.corrRF
Author: Elliot H. Young [aut, cre]
Maintainer: Elliot H. Young <ey244 at cam.ac.uk>
License: GPL-3
NeedsCompilation: yes
CRAN checks: corrRF results

Documentation:

Reference manual: corrRF.pdf

Downloads:

Package source: corrRF_1.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: corrRF_1.1.0.zip
macOS binaries: r-devel (arm64): corrRF_1.1.0.tgz, r-release (arm64): corrRF_1.1.0.tgz, r-oldrel (arm64): corrRF_1.1.0.tgz, r-devel (x86_64): corrRF_1.1.0.tgz, r-release (x86_64): corrRF_1.1.0.tgz, r-oldrel (x86_64): corrRF_1.1.0.tgz

Linking:

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