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grf: Generalized Random Forests
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.
Getting started
Browse package contents
Package details |
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| Author | Julie Tibshirani [aut, cre], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], David Hirshberg [ctb], Luke Miner [ctb], Erik Sverdrup [aut], Stefan Wager [aut], Marvin Wright [ctb] |
| Maintainer | Julie Tibshirani <jtibs@cs.stanford.edu> |
| License | GPL-3 |
| Version | 2.3.1 |
| URL | https://github.com/grf-labs/grf |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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