Package: grf
Title: Generalized Random Forests (Beta)
Version: 0.10.3
Author: Julie Tibshirani [aut, cre],
    Susan Athey [aut],
    Rina Friedberg [ctb],
    Vitor Hadad [ctb],
    Luke Miner [ctb],
    Stefan Wager [aut],
    Marvin Wright [ctb]
BugReports: https://github.com/grf-labs/grf/issues
Maintainer: Julie Tibshirani <jtibs@cs.stanford.edu>
Description: A pluggable package for forest-based statistical estimation and inference.
    GRF currently provides methods for non-parametric least-squares regression,
    quantile regression, and treatment effect estimation (optionally using instrumental
    variables). This package is currently in beta, and we expect to make continual
    improvements to its performance and usability.
Depends: R (>= 3.3.0)
License: GPL-3
LinkingTo: Rcpp, RcppEigen
Imports: DiceKriging, lmtest, Matrix, methods, Rcpp (>= 0.12.15),
        sandwich (>= 2.4-0)
RoxygenNote: 6.1.1
Suggests: DiagrammeR, testthat
SystemRequirements: GNU make
URL: https://github.com/grf-labs/grf
NeedsCompilation: yes
Packaged: 2019-05-27 04:32:06 UTC; jtibshirani
Repository: CRAN
Date/Publication: 2019-05-27 05:00:07 UTC
Built: R 3.6.1; x86_64-w64-mingw32; 2019-07-21 06:21:58 UTC; windows
Archs: x64
