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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: 2.4.0
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: 2024-11-15
DOI: 10.32614/CRAN.package.grf
Author: Julie Tibshirani [aut], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], David Hirshberg [ctb], Luke Miner [ctb], Erik Sverdrup [aut, cre], Stefan Wager [aut], Marvin Wright [ctb]
Maintainer: Erik Sverdrup <erik.sverdrup at monash.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_2.4.0.tar.gz
Windows binaries: r-devel: grf_2.4.0.zip, r-release: grf_2.4.0.zip, r-oldrel: grf_2.4.0.zip
macOS binaries: r-release (arm64): grf_2.4.0.tgz, r-oldrel (arm64): grf_2.4.0.tgz, r-release (x86_64): grf_2.4.0.tgz, r-oldrel (x86_64): grf_2.4.0.tgz
Old sources: grf archive

Reverse dependencies:

Reverse imports: aggTrees, causalweight, EpiForsk, evalITR, htetree, longsurr, OutcomeWeights, policytree, qeML, roseRF
Reverse suggests: CRE, maq, targeted

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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