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High-Performance Open-Source Archive

CRAN: Package roseRF

roseRF: ROSE Random Forests for Robust Semiparametric Efficient Estimation

ROSE (RObust Semiparametric Efficient) random forests for robust semiparametric efficient estimation in partially parametric models (containing generalised partially linear models). Details can be found in the paper by Young and Shah (2024) <doi:10.48550/arXiv.2410.03471>.

Version: 0.1.0
Depends: R (≥ 4.2.0)
Imports: caret (≥ 6.0.93), glmnet (≥ 4.1.6), keras, mgcv, mlr (≥ 2.19.1), ParamHelpers, ranger (≥ 0.14.1), grf, rpart, stats, tuneRanger (≥ 0.5), xgboost
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-10-11
DOI: 10.32614/CRAN.package.roseRF
Author: Elliot H. Young [aut, cre], Rajen D. Shah [aut]
Maintainer: Elliot H. Young <ey244 at cam.ac.uk>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: roseRF results

Documentation:

Reference manual: roseRF.html , roseRF.pdf

Downloads:

Package source: roseRF_0.1.0.tar.gz
Windows binaries: r-devel: roseRF_0.1.0.zip, r-release: roseRF_0.1.0.zip, r-oldrel: roseRF_0.1.0.zip
macOS binaries: r-release (arm64): roseRF_0.1.0.tgz, r-oldrel (arm64): roseRF_0.1.0.tgz, r-release (x86_64): roseRF_0.1.0.tgz, r-oldrel (x86_64): roseRF_0.1.0.tgz

Linking:

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

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