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 |
| Author: |
Elliot H. Young [aut, cre] |
| Maintainer: |
Elliot H. Young <ey244 at cam.ac.uk> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| CRAN checks: |
corrRF results |
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