grf: Generalized Random Forests (Beta)

A pluggable package for forest-based statistical estimation and inference. GRF currently provides methods for non-parametric least-squares regression, quantile regression, and treatment effect estimation (optionally using instrumental variables). This package is currently in beta, and we expect to make continual improvements to its performance and usability.

Version: 0.10.3
Depends: R (≥ 3.3.0)
Imports: DiceKriging, lmtest, Matrix, methods, Rcpp (≥ 0.12.15), sandwich (≥ 2.4-0)
LinkingTo: Rcpp, RcppEigen
Suggests: DiagrammeR, testthat
Published: 2019-05-27
Author: Julie Tibshirani [aut, cre], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], Luke Miner [ctb], Stefan Wager [aut], Marvin Wright [ctb]
Maintainer: Julie Tibshirani <jtibs at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: GNU make
In views: MachineLearning
CRAN checks: grf results


Reference manual: grf.pdf
Package source: grf_0.10.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: grf_0.10.3.tgz, r-oldrel: grf_0.10.3.tgz
Old sources: grf archive

Reverse dependencies:

Reverse imports: StratifiedMedicine
Reverse suggests: uplifteval


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