Generalized Random Forests

A pluggable package for forest-based statistical estimation and inference. GRF currently provides methods for non-parametric least-squares regression, quantile regression, survival regression and treatment effect estimation (optionally using instrumental variables), with support for missing values.

News

Reference manual

install.packages("grf")

1.2.0 by Julie Tibshirani, 10 months ago

https://github.com/grf-labs/grf

Report a bug at https://github.com/grf-labs/grf/issues

Browse source code at https://github.com/cran/grf

Authors: Julie Tibshirani [aut, cre] , Susan Athey [aut] , Rina Friedberg [ctb] , Vitor Hadad [ctb] , David Hirshberg [ctb] , Luke Miner [ctb] , Erik Sverdrup [ctb] , Stefan Wager [aut] , Marvin Wright [ctb]

Documentation: PDF Manual

Task views: Machine Learning & Statistical Learning, Missing Data

GPL-3 license

Imports DiceKriging, lmtest, Matrix, methods, Rcpp, sandwich

Suggests DiagrammeR, testthat

Linking to Rcpp, RcppEigen

System requirements: GNU make

Imported by policytree, postDoubleR.

Suggested by uplifteval.

See at CRAN