Generalized Random Forests R package grf version 2.6.1 CRAN Task View: CausalInference (https://CRAN.R-project.org/view=CausalInference) CRAN Task View: Econometrics (https://CRAN.R-project.org/view=Econometrics) CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning) CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) 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. Software Depends: R (>= 3.5.0) Imports: DiceKriging, lmtest, Matrix, methods, Rcpp (>= 0.12.15), sandwich (>= 2.4-0) LinkingTo: Rcpp, RcppEigen Suggests: DiagrammeR, MASS, policytree, rdrobust, survival (>= 3.2-8), testthat (>= 3.0.4), knitr, rmarkdown Erik Sverdrup <erik.sverdrup@monash.edu> Comprehensive R Archive Network (CRAN) 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] GPL-3 2026-03-04 application/tgz https://CRAN.R-project.org/package=grf doi:10.32614/CRAN.package.grf