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.
Version: | 0.9.4 |
Depends: | R (≥ 3.3.1) |
Imports: | Rcpp (≥ 0.12.10) |
LinkingTo: | Rcpp |
Suggests: | sandwich, testthat |
Published: | 2017-11-27 |
Author: | Julie Tibshirani [aut, cre], Susan Athey [aut], Stefan Wager [aut], Marvin Wright [ctb], all contributors to the included version of Eigen [ctb] |
Maintainer: | Julie Tibshirani <jtibs at cs.stanford.edu> |
BugReports: | https://github.com/swager/grf/issues |
License: | GPL-3 |
URL: | https://github.com/swager/grf |
NeedsCompilation: | yes |
SystemRequirements: | GNU make |
CRAN checks: | grf results |
Reference manual: | grf.pdf |
Package source: | grf_0.9.4.tar.gz |
Windows binaries: | r-devel: grf_0.9.4.zip, r-release: grf_0.9.4.zip, r-oldrel: grf_0.9.4.zip |
OS X El Capitan binaries: | r-release: grf_0.9.4.tgz |
OS X Mavericks binaries: | r-oldrel: grf_0.9.4.tgz |
Old sources: | grf archive |
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