High-Performance Open-Source Archive
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 |
| Reference manual: | roseRF.html , roseRF.pdf |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=roseRF to link to this page.
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