RegEnRF
Regression-Enhanced Random Forests
A novel generalized Random Forest method, that can improve on RFs by borrowing the strength of penalized parametric regression. Based on Zhang et al. (2019) <doi:10.48550/arXiv.1904.10416>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | RegEnRF_1.0.0.tar.gz |
22.3 KiB |
1.0.0 |
rolling linux/noble R-4.5 | RegEnRF_1.0.0.tar.gz |
22.3 KiB |
1.0.0 |
rolling source/ R- | RegEnRF_1.0.0.tar.gz |
13.1 KiB |
1.0.0 |
latest linux/jammy R-4.5 | RegEnRF_1.0.0.tar.gz |
22.3 KiB |
1.0.0 |
latest linux/noble R-4.5 | RegEnRF_1.0.0.tar.gz |
22.3 KiB |
1.0.0 |
latest source/ R- | RegEnRF_1.0.0.tar.gz |
13.1 KiB |
1.0.0 |
2026-04-26 source/ R- | RegEnRF_1.0.0.tar.gz |
13.1 KiB |
1.0.0 |
2026-04-23 source/ R- | RegEnRF_1.0.0.tar.gz |
13.1 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | RegEnRF_1.0.0.zip |
25.9 KiB |
Dependencies (latest)
Imports
Suggests
- testthat (>= 3.0.0)