grf: Generalized Random Forests

Forest-based statistical estimation and inference. GRF provides non-parametric methods for heterogeneous treatment effects estimation (optionally using right-censored outcomes, multiple treatment arms or outcomes, or instrumental variables), as well as least-squares regression, quantile regression, and survival regression, all with support for missing covariates.

Version: 2.2.0
Depends: R (≥ 3.5.0)
Imports: DiceKriging, lmtest, Matrix, methods, Rcpp (≥ 0.12.15), sandwich (≥ 2.4-0)
LinkingTo: Rcpp, RcppEigen
Suggests: DiagrammeR, MASS, rdd, survival (≥ 3.2-8), testthat (≥ 3.0.4)
Published: 2022-08-06
Author: Julie Tibshirani [aut, cre], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], David Hirshberg [ctb], Luke Miner [ctb], Erik Sverdrup [aut], Stefan Wager [aut], Marvin Wright [ctb]
Maintainer: Julie Tibshirani <jtibs at cs.stanford.edu>
BugReports: https://github.com/grf-labs/grf/issues
License: GPL-3
URL: https://github.com/grf-labs/grf
NeedsCompilation: yes
SystemRequirements: GNU make
In views: CausalInference, Econometrics, MachineLearning, MissingData
CRAN checks: grf results

Documentation:

Reference manual: grf.pdf

Downloads:

Package source: grf_2.2.0.tar.gz
Windows binaries: r-devel: grf_2.2.0.zip, r-release: grf_2.2.0.zip, r-oldrel: grf_2.2.0.zip
macOS binaries: r-release (arm64): grf_2.2.0.tgz, r-oldrel (arm64): grf_2.2.0.tgz, r-release (x86_64): grf_2.2.0.tgz, r-oldrel (x86_64): grf_2.2.0.tgz
Old sources: grf archive

Reverse dependencies:

Reverse imports: longsurr, policytree
Reverse suggests: rdddr, targeted

Linking:

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