Package: grf
Title: Generalized Random Forests
Version: 2.6.1
Authors@R: c(
    person("Julie", "Tibshirani", role = "aut", email = "jtibs@cs.stanford.edu"),
    person("Susan", "Athey", role = "aut"),
    person("Rina", "Friedberg", role = "ctb"),
    person("Vitor", "Hadad", role = "ctb"),
    person("David", "Hirshberg", role = "ctb"),
    person("Luke", "Miner", role = "ctb"),
    person("Erik", "Sverdrup", role = c("aut", "cre"), email = "erik.sverdrup@monash.edu"),
    person("Stefan", "Wager", role = "aut"),
    person("Marvin", "Wright", role = "ctb")
    )
BugReports: https://github.com/grf-labs/grf/issues
Description: 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.
Depends: R (>= 3.5.0)
License: GPL-3
LinkingTo: Rcpp, RcppEigen
Imports: DiceKriging, lmtest, Matrix, methods, Rcpp (>= 0.12.15),
        sandwich (>= 2.4-0)
RoxygenNote: 7.3.3
Suggests: DiagrammeR, MASS, policytree, rdrobust, survival (>= 3.2-8),
        testthat (>= 3.0.4), knitr, rmarkdown
SystemRequirements: C++17, GNU make
URL: https://github.com/grf-labs/grf
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-03-03 19:28:41 UTC; erikcs
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@monash.edu>
Repository: CRAN
Date/Publication: 2026-03-04 06:30:43 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2026-03-20 18:42:25 UTC; windows
Archs: x64
