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.


Reference manual

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1.2.0 by Julie Tibshirani, 4 months ago

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Browse source code at

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

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