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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: corrRF_1.1.0.zip, r-release: corrRF_1.1.0.zip, 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:

Please use the canonical form https://CRAN.R-project.org/package=corrRF to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.