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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.

Versions across snapshots

VersionRepositoryFileSize
2.6.1 rolling linux/jammy R-4.5 grf_2.6.1.tar.gz 1.1 MiB
2.6.1 rolling linux/noble R-4.5 grf_2.6.1.tar.gz 1.2 MiB
2.6.1 rolling source/ R- grf_2.6.1.tar.gz 613.0 KiB
2.6.1 latest linux/jammy R-4.5 grf_2.6.1.tar.gz 1.1 MiB
2.6.1 latest linux/noble R-4.5 grf_2.6.1.tar.gz 1.2 MiB
2.6.1 latest source/ R- grf_2.6.1.tar.gz 613.0 KiB
2.6.1 2026-04-26 source/ R- grf_2.6.1.tar.gz 613.0 KiB
2.6.1 2026-04-23 source/ R- grf_2.6.1.tar.gz 613.0 KiB
2.6.1 2026-04-09 windows/windows R-4.5 grf_2.6.1.zip 1.5 MiB
2.4.0 2025-04-20 source/ R- grf_2.4.0.tar.gz 204.3 KiB

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