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 |
Reference manual: | grf.pdf |
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 imports: | aggTrees, causalweight, EpiForsk, evalITR, htetree, longsurr, OutcomeWeights, policytree, qeML, roseRF |
Reverse suggests: | CRE, maq, targeted |
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