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randomForestSRC
Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
View on CRAN: Click
here
Download and install randomForestSRC package within the R console
Install from CRAN:
install.packages("randomForestSRC")
Install from Github:
library("remotes")
install_github("cran/randomForestSRC") Install by package version:
library("remotes")
install_version("randomForestSRC", "3.5.0") Attach the package and use:
library("randomForestSRC")
Maintained by
Udaya B. Kogalur
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-10-31
Latest Update: 2025-06-08
Description:
Fast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. New Mahalanobis splitting for correlated outcomes. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and standard errors for variable importance. New improved holdout importance. Case-specific importance. Minimal depth variable importance. Visualize trees on your Safari or Google Chrome browser. Anonymous random forests for data privacy.
How to cite:
Udaya B. Kogalur (2012). randomForestSRC: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC). R package version 3.5.0, https://cran.r-project.org/web/packages/randomForestSRC. Accessed 05 Mar. 2026.
Previous versions and publish date:
1.0.0 (2012-10-31 17:21), 1.0.1 (2012-11-13 21:42), 1.0.2 (2012-12-07 07:40), 1.1.0 (2013-02-25 20:16), 1.2 (2013-04-30 06:28), 1.3 (2013-07-22 17:23), 1.4 (2013-12-10 23:06), 1.5.0 (2014-05-13 07:54), 1.5.1 (2014-05-16 07:38), 1.5.2 (2014-06-05 06:56), 1.5.3 (2014-06-25 07:14), 1.5.4 (2014-07-14 15:13), 1.5.5 (2014-08-26 16:11), 1.6.0 (2015-01-12 23:15), 1.6.1 (2015-03-04 21:35), 2.0.0 (2015-12-07 11:09), 2.0.5 (2015-12-24 13:47), 2.0.7 (2016-01-15 19:45), 2.1.0 (2016-03-17 18:59), 2.2.0 (2016-05-17 00:41), 2.3.0 (2016-09-07 08:58), 2.4.0 (2016-11-03 00:29), 2.4.1 (2016-11-06 00:19), 2.4.2 (2017-03-07 15:02), 2.5.0 (2017-08-07 08:02), 2.5.1 (2017-10-17 23:35), 2.6.0 (2018-05-02 13:58), 2.6.1 (2018-05-18 14:42), 2.7.0 (2018-08-18 00:10), 2.8.0 (2019-01-02 17:20), 2.9.0 (2019-04-22 18:10), 2.9.1 (2019-07-08 21:00), 2.9.2 (2019-11-18 19:20), 2.9.3 (2020-01-21 08:50), 2.10.0 (2021-01-31 19:10), 2.10.1 (2021-02-10 16:00), 2.11.0 (2021-03-31 07:10), 2.12.0 (2021-07-08 12:00), 2.12.1 (2021-09-05 21:10), 2.13.0 (2021-10-15 16:10), 2.14.0 (2021-11-11 16:20), 3.0.0 (2022-01-04 00:00), 3.0.1 (2022-02-14 10:50), 3.0.2 (2022-03-02 01:10), 3.1.0 (2022-04-15 16:50), 3.1.1 (2022-07-06 22:30), 3.2.0 (2023-01-12 11:30), 3.2.1 (2023-03-03 19:30), 3.2.2 (2023-05-24 01:12), 3.2.3 (2023-12-06 15:30), 3.3.0 (2024-06-25 14:30), 3.3.1 (2024-07-25 16:30), 3.3.2 (2025-01-14 02:20), 3.3.3 (2025-01-16 10:20), 3.4.0 (2025-05-26 08:00), 3.4.1 (2025-06-08 02:00), 3.4.2 (2025-09-30 13:40), 3.4.3 (2025-10-10 07:30), 3.4.4 (2025-11-05 18:40), 3.4.5 (2025-11-26 07:20), 3.5.0 (2026-01-11 11:20)
Other packages that cited randomForestSRC R package
View randomForestSRC citation profile
Other R packages that randomForestSRC depends,
imports, suggests or enhances
Complete documentation for randomForestSRC
Functions, R codes and Examples using
the randomForestSRC R package
Some associated functions: breast . find.interaction.rfsrc . follic . get.tree.rfsrc . hd . holdout.vimp.rfsrc . housing . imbalanced.rfsrc . impute.rfsrc . max.subtree.rfsrc . nutrigenomic . partial.rfsrc . pbc . peakVO2 . plot.competing.risk.rfsrc . plot.quantreg.rfsrc . plot.rfsrc . plot.subsample.rfsrc . plot.survival.rfsrc . plot.variable.rfsrc . predict.rfsrc . print.rfsrc . quantreg.rfsrc . randomForestSRC_package . rfsrc.anonymous . rfsrc.fast . rfsrc.news . rfsrc . sidClustering.rfsrc . stat.split.rfsrc . subsample.rfsrc . synthetic.rfsrc . tune.rfsrc . var.select.rfsrc . vdv . veteran . vimp.rfsrc . wihs . wine .
Some associated R codes: distance.R . find.interaction.rfsrc.R . generic.impute.rfsrc.R . generic.predict.rfsrc.R . get.tree.rfsrc.R . holdout.vimp.rfsrc.R . imbalanced.rfsrc.R . impute.rfsrc.R . max.subtree.rfsrc.R . partial.rfsrc.R . plot.competing.risk.rfsrc.R . plot.quantreg.rfsrc.R . plot.rfsrc.R . plot.subsample.rfsrc.R . plot.survival.rfsrc.R . plot.variable.rfsrc.R . predict.rfsrc.R . print.rfsrc.R . quantreg.rfsrc.R . rfsrc.R . rfsrc.anonymous.R . rfsrc.cart.R . rfsrc.fast.R . rfsrc.news.R . sidClustering.rfsrc.R . stat.split.rfsrc.R . subsample.rfsrc.R . synthetic.rfsrc.R . tune.nodesize.rfsrc.R . tune.rfsrc.R . utilities.R . utilities.data.R . utilities.factor.R . utilities.imbalanced.R . utilities.impute.R . utilities.multivariate.R . utilities.performance.R . utilities.predict.R . utilities.quantreg.R . utilities.sgreedy.R . utilities.subsample.R . utilities.subsample.bootstrap.R . utilities.survival.R . utilities.tdc.R . utilities.unsupervised.R . utilities.varselect.R . var.select.rfsrc.R . vimp.rfsrc.R . zzz.R . Full randomForestSRC package functions and examples
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