R Observatory: Metrics for RfEmpImp version 2.1.8

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

RfEmpImp

2.1.8

Multiple Imputation using Chained Random Forests

0packages depend

2.5Kdownloads / year

81.7%test coverage

11/13checks pass

Overview

About

Maintained by Shangzhi HongFirst published 2020-05-163 releasesCRAN page ↗GitHub ↗

An R package for multiple imputation using chained random forests. Implemented methods can handle missing data in mixed types of variables by using prediction-based or node-based conditional distributions constructed using random forests. For prediction-based imputation, the method based on the empirical distribution of out-of-bag prediction errors of random forests and the method based on normality assumption for prediction errors of random forests are provided for imputing continuous variables. And the method based on predicted probabilities is provided for imputing categorical variables. For node-based imputation, the method based on the conditional distribution formed by the predicting nodes of random forests, and the method based on proximity measures of random forests are provided. More details of the statistical methods can be found in Hong et al. (2020) arXiv:2004.14823.

Install

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

install.packages("RfEmpImp", 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("shangzhi-hong/RfEmpImp")

Development version from shangzhi-hong/RfEmpImp. 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-rfempimp

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

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-RfEmpImp

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-RfEmpImp

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

2NOTE11OK

Failing flavors

NOTE r-devel-linux-x86_64-debian-clang
NOTE r-devel-linux-x86_64-debian-gcc

Slowest check: 2.9 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 0.73

81.7%

Coverage · measured lines

100%

Documentation · exports

2

Dependencies · direct

Check history

NOTE2026-06-09
11 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-06-08
11 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-05-02
11 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-04-25
9 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-03-10
12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 100%
References docs: 53%

Downloads

2.5K

CRAN downloads in the past year

Rank #16,485 · ~7/day · ~210/mo

Releases R versions

Daily download trend is not available in this view yet.

17430 days

64690 days

2.5K1 year

Compare downloads with other packages →

Also on117 r2u14 autocran25 c2d4u

Repository

GitHub ↗ shangzhi-hong/rfempimp

5Stars

2Forks

0Open issues

0Open PRs

5Releases

83Commits

2Contributors

imputationmissing-datarandom-forest

83 commits · Last activity 2022-10-20

Stars over time

2024-06-26 · 42026-07-07 · 5

Repository practices

Upstream repositoryBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/shangzhi-hong/rfempimp on 2026-08-16.

Docs source (1)

README.Rmd

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

5 external dependencies (excludes base and recommended)

Depends (3)

R >= 3.5.0mice ranger

Imports (0)

none

LinkingTo (0)

none

Suggests (3)

testthat knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (2)

Maintainer (1)

Shangzhi Hong

Author, Maintainer

Authors (1)

Shangzhi Hong

Author, Maintainer

Other (1)

Henry S. Lynn

Thesis advisor

Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
2.1.8Latest
2022-10-20 · current release · diff ↗
unarchivedReturned to CRAN
2022-10-20
archivedRemoved from CRAN
2022-10-03
check issues were not corrected despite reminders
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
2.1.5
2020-06-25 · diff ↗
2.0.3
2020-05-16
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2020-05-16
Total releases: 3 / 6 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.5.0
Download size: 149 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Missing Data

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("RfEmpImp")

Format

Hong, S., & Lynn, H. S. (2022). RfEmpImp: Multiple Imputation using Chained Random Forests (Version 2.1.8) [Computer software]. https://doi.org/10.32614/CRAN.package.RfEmpImp

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 RfEmpImp version 2.1.8 [Data set]. HJJB, LLC. Data release v2026-08-16. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-16, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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