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RfEmpImp

2.1.8

Multiple Imputation using Chained Random Forests

0packages depend
2.6Kdownloads / 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

Health

CRAN checks
2NOTE11OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-clang
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 3.2 min · r-devel-linux-x86_64-fedora-clang
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

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
53%

Downloads

2.6K
CRAN downloads in the past year
Rank #16,296 · ~7/day · ~215/mo
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19330 days
70290 days
2.6K1 year
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Repository

Repository
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 2026-07-19.

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 >= 3.5.0miceranger
Imports (0)
none
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Other (1)
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
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