CRAN/E | grf

grf

Generalized Random Forests

Installation

About

Forest-based statistical estimation and inference. GRF provides non-parametric methods for heterogeneous treatment effects estimation (optionally using right-censored outcomes, multiple treatment arms or outcomes, or instrumental variables), as well as least-squares regression, quantile regression, and survival regression, all with support for missing covariates.

github.com/grf-labs/grf
System requirements GNU make
Bug report File report

Key Metrics

Version 2.3.2
R ≥ 3.5.0
Published 2024-02-25 64 days ago
Needs compilation? yes
License GPL-3
CRAN checks grf results

Downloads

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Maintainer

Maintainer

Erik Sverdrup

erik.sverdrup@monash.edu

Authors

Julie Tibshirani

aut

Susan Athey

aut

Rina Friedberg

ctb

Vitor Hadad

ctb

David Hirshberg

ctb

Luke Miner

ctb

Erik Sverdrup

aut / cre

Stefan Wager

aut

Marvin Wright

ctb

Material

Reference manual
Package source

In Views

CausalInference
Econometrics
MachineLearning
MissingData

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

grf archive

Depends

R ≥ 3.5.0

Imports

DiceKriging
lmtest
Matrix
methods
Rcpp ≥ 0.12.15
sandwich ≥ 2.4-0

Suggests

DiagrammeR
MASS
rdd
survival ≥ 3.2-8
testthat ≥3.0.4

LinkingTo

Rcpp
RcppEigen

Reverse Imports

aggTrees
causalweight
evalITR
htetree
longsurr
policytree
qeML

Reverse Suggests

CRE
maq
rdss
targeted