Generalized Random Forests (Beta)

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.


Reference manual

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0.10.2 by Julie Tibshirani, 5 months ago

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Browse source code at

Authors: Julie Tibshirani [aut, cre] , Susan Athey [aut] , Stefan Wager [aut] , Rina Friedberg [ctb] , Luke Miner [ctb] , Marvin Wright [ctb]

Documentation:   PDF Manual  

Task views: Machine Learning & Statistical Learning

GPL-3 license

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

Suggests testthat

Linking to Rcpp, RcppEigen

System requirements: GNU make

See at CRAN