R Observatory: Metrics for randomForestSRC version 3.9.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

randomForestSRC

3.9.0Package record

Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)

18packages dependsuggested by 14

91.3Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Udaya B. KogalurCRAN page ↗GitHub ↗Website ↗Issues ↗

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.

Changes in 3.9.0

Forest storage and imputation

Added optional compact = TRUE saving to fast.save() and fast.save.list(). Compact saves omit terminal-node information and reconstruct it during prediction without growing new trees. This can reduce disk use at the cost of additional prediction time. The fitted object is unchanged, and both saving modes use the existing loaders. The default remains compact = FALSE.
Added compact-save eligibility checks before removing an existing destination, including checks of every forest when saving a list. Compact saving requires a non-anonymous forest with retained training predictors and responses, and a sampling-size specification that preserves the training sample size after loading. fast.save() also checks the grow-object class before removing its destination.

Show all changes in 3.9.0Hide the rest of the changes in 3.9.0

impute.learn() now accepts terminal.qualts and terminal.quants in full.sweep.options, allowing terminal-node storage controls to reach the saved target learners. These settings are independent of initial-imputation and supervised auxiliary-forest options.

Documentation and build

Reorganized and clarified help for forest saving and loading, imputation and OOD scoring, quantile regression, survival and classification performance, multivariate extraction, partial dependence, subsampling, tuning, and associated plots. Expanded explanations of prediction selection, score and interval interpretation, returned values, graphical controls, and examples.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("randomForestSRC", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("kogalur/randomForestSRC")

Development version from kogalur/randomForestSRC. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-randomforestsrc

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-randomForestSRC

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-randomForestSRC

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 5.1 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-07
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 3.9.0

READMENoVignettesNoNEWSYes · 67% structured · mentions 3.9.0Citation fileYes · cites a publicationWebsiteYes

Help pages: 39includes a package overview page
Examples that run: 27%10 run in a plain check (1 of them under a condition) · 27 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 96%
Documented parameters: 77%
Return-value docs: 89%
Help pages citing references: 77%

How these are measured

Downloads

91.3K

CRAN downloads in the past year

Rank #1,371 · ~250/day · ~7.6K/mo

Releases R versions

Daily download trend is not available in this view yet.

7.1K30 days

20.1K90 days

91.3K1 year

Compare downloads with other packages →

Also on1.7K r2u5 autocran16.7K conda_forge189 c2d4u

How downloads are counted

Repository

kogalur/randomforestsrc ↗Account: kogalur

135Stars

22Forks

44Open issues

0Open PRs

0Releases

73Commits

3Commit identities

73 commits · Last activity 2026-10-13 · 0% stars, 30d · Default branch at 3.9.1, ahead of CRAN 3.9.0 (checked 2026-10-18) · Discussions: 185 posts

Responsiveness

How these are sampled

PRs merged (all time): 0%
Median days to close, 50 most recently updated closed issues: 1
Median days to close, 50 most recently updated closed PRs: 269

Stars over time

2025-08-17 · 1282026-07-16 · 135

How these are measured

PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/kogalur/randomforestsrc on 2026-10-18.

Docs source (1)

GitHub Pages site last deployed 2021-08-20

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

9 external dependencies (excludes base and recommended)

Installing randomForestSRC adds 62 packages (31 with compiled code, 51 MB of source tarballs). Heaviest: stringi 11 MB, bslib 5.6 MB, igraph 4.8 MB.

Depends (1)

R >= 4.3.0

Imports (3)

paralleldata.tree DiagrammeR

LinkingTo (0)

none

Suggests (9)

survivalpec prodlim mlbench interp caretclusterfst data.table

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

18direct

0indirect

Imports 18

Suggested by 14

Show all 32 packagesHide all 32 packages

Depends, Imports or LinkingTo, most downloaded first

varPro ggRandomForests glmnetr E2E AutoScore randomForestRHF boostmtree ranktreeEnsemble CoxAIPW cjbart precmed survalis SIMMS survivalSL randomForestSGT pacheck tehtuner survcompare

Suggests, most downloaded first

riskRegression tram targeted SurvMetrics MachineShop peperr familiar pmsims survex mlrCPO SuperSurv AutoMLR UKBAnalytica PheCAP

How these are counted

Code & Tests

Datasets

People & History

People (2)

Udaya B. Kogalur

Author, Maintainer since 1.0.0 (2012)

Hemant Ishwaran

Author

Releases (70)

Pick two releases to compare their code metrics.

3.9.0Latest
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2026-09-22 · current release · diff ↗
3.8.0
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2026-09-16 · diff ↗ ·
removed 1 export
lsos

added 1 export
get.pinball.error
3.7.0
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2026-08-31 · diff ↗ ·
added 2 exports
get.auct.survival, plotBrierAUC
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R 4.6.0 released · 2026-04-24
3.6.2
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2026-04-19 · diff ↗
3.6.1
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2026-04-10 · diff ↗ ·
added 2 exports
impute.ood.rfsrc, impute.ood
3.6.0
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2026-03-25 · diff ↗ ·
added 6 exports
impute.learn, impute.learn.rfsrc, load.impute.learn, load.impute.learn.rfsrc, save.impute.learn, save.impute.learn.rfsrc
3.5.1
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2026-02-12 · diff ↗
3.5.0
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3.4.5
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3.4.2
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2025-09-30 · diff ↗ ·
removed 6 exports
find.interaction, find.interaction.rfsrc, synthetic.rfsrc, synthetic, stat.split, stat.split.rfsrc

added 1 export
print.imbalanced.performance
3.4.1
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2025-06-08 · diff ↗
3.4.0
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2025-05-26 · diff ↗ ·
removed 2 exports
var.select, var.select.rfsrc

added 5 exports
fast.save, fast.load, fast.save.list, fast.load.list, lsos
R
R 4.5.0 released · 2025-04-11

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3.3.3
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2025-01-16 · diff ↗
3.3.2
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3.3.1
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2024-07-25 · diff ↗ ·
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3.3.0
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R 4.4.0 released · 2024-04-24
3.2.3
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2023-12-06 · diff ↗
3.2.2
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2023-05-24 · diff ↗ ·
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print.bootsample, print.bootsample.rfsrc, print.subsample, print.subsample.rfsrc
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R 4.3.0 released · 2023-04-21
3.2.1
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3.1.1
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R 4.2.0 released · 2022-04-22
3.1.0
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2022-04-15 · diff ↗
unarchivedReturned to CRAN
2022-03-02
archivedRemoved from CRAN
2022-02-23
check problems were not corrected in time
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R 4.1.0 released · 2021-05-18
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R 4.0.0 released · 2020-04-24
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R 3.6.0 released · 2019-04-26
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R 3.5.0 released · 2018-04-23
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R 3.4.0 released · 2017-04-21
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R 3.3.0 released · 2016-05-03
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R 3.2.0 released · 2015-04-16
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R 3.1.0 released · 2014-04-10
3.0.3
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3.0.2
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3.0.1
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3.0.0
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R 3.0.0 released · 2013-04-03
2.15.3
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2013-02-25 · diff ↗
2.14.0
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2021-11-11 · diff ↗ ·
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get.brier.survival, get.pr.auc, get.pr.curve, get.rfq.threshold
2.13.0
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2021-10-15 · diff ↗ ·
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get.imbalanced.optimize
2.12.1
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2021-09-05 · diff ↗
2.12.0
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2021-07-08 · diff ↗ ·
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get.imbalanced.performance, get.partial.plot.data
2.11.0
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2021-03-31 · diff ↗ ·
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get.mv.cserror, get.mv.csvimp, rfsrc.anonymous
2.10.1
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2.10.0
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get.tree, get.tree.rfsrc, sid.perf.metric, sidClustering, sidClustering.rfsrc
2.9.3
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2.9.2
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2.9.0
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2019-04-22 · diff ↗ ·
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cindex, quantileReg, quantileReg.rfsrc, rfsrcFast, rfsrcFast.rfsrc, rfsrcSyn, rfsrcSyn.rfsrc

added 22 exports
extract.quantile, get.auc, get.bayes.rule, get.brier.error, get.cindex, get.confusion, get.misclass.error, get.quantile, get.quantile.crps, get.quantile.stat, holdout.vimp, holdout.vimp.rfsrc, plot.quantreg, plot.quantreg.rfsrc, quantreg, quantreg.rfsrc, rfsrc.cart, rfsrc.fast, synthetic.rfsrc, synthetic, tune.nodesize, tune.nodesize.rfsrc
2.8.0
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2019-01-02 · diff ↗ ·
added 2 exports
imbalanced, imbalanced.rfsrc
2.7.0
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2018-08-18 · diff ↗ ·
added 11 exports
extract.bootsample, extract.subsample, get.mv.error.block, plot.subsample, plot.subsample.rfsrc, rfsrcFast, rfsrcFast.rfsrc, subsample, subsample.rfsrc, tune, tune.rfsrc
2.6.1
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2018-05-18 · diff ↗
2.6.0
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2018-05-02 · diff ↗ ·
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get.mv.formula
2.5.1
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2017-10-17 · diff ↗
2.5.0
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2017-08-07 · diff ↗ ·
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rf2rfz

added 7 exports
cindex, get.mv.error, get.mv.predicted, get.mv.vimp, partial, quantileReg, quantileReg.rfsrc
2.4.2
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2017-03-07 · diff ↗
2.4.1
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2.4.0
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2016-11-03 · diff ↗ ·
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partial.rfsrc
2.3.0
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2.1.0
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2.0.7
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2.0.5
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2015-12-24 · diff ↗ ·
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impute
2.0.0
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2015-12-07 · diff ↗
1.6.1
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1.5.4
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2014-07-14 · diff ↗ ·
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stat.split.rfsrc, stat.split
1.5.3
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2014-06-25 · diff ↗ ·
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rfsrcSyn.rfsrc, rfsrcSyn
1.5.2
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2014-06-05 · diff ↗
1.5.1
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2014-05-16 · diff ↗
1.5.0
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2014-05-13 · diff ↗
1.4
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2013-12-10 · diff ↗ ·
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restore.rfsrc, restore
1.3
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1.1.0
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2013-02-25 · diff ↗
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1.0.1
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2012-11-13 · diff ↗
1.0.0
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2012-10-31
R
R 2.15.0 released · 2012-03-30

Package metadata

First published: 2012-10-31
Total releases: 70 / 14 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 4.3.0
Bundled data: 851 KB / 11 files
Download size: 1.3 MB

Appears in task views

High-Performance and Parallel Computing with R Machine Learning & Statistical Learning Survival Analysis

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("randomForestSRC")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for randomForestSRC version 3.9.0 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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