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ClustImpute

0.2.4

K-Means Clustering with Build-in Missing Data Imputation

1packages depend
4.3Kdownloads / year
100.0%test coverage
11/13checks pass

Overview

About
Maintained by Oliver PfaffelFirst published 2019-08-017 releasesCRAN page ↗

This k-means algorithm is able to cluster data with missing values and as a by-product completes the data set. The implementation can deal with missing values in multiple variables and is computationally efficient since it iteratively uses the current cluster assignment to define a plausible distribution for missing value imputation. Weights are used to shrink early random draws for missing values (i.e., draws based on the cluster assignments after few iterations) towards the global mean of each feature. This shrinkage slowly fades out after a fixed number of iterations to reflect the increasing credibility of cluster assignments. See the vignette for details.

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: 2.4 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.56
100.0%
Coverage · measured lines
80%
Documentation · exports
8
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
  • NOTE2026-03-10
    12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 474 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

4.3K
CRAN downloads in the past year
Rank #10,987 · ~12/day · ~356/mo
Daily download trend is not available in this view yet.
21930 days
88990 days
4.3K1 year
Compare downloads with other packages →
Also on132 r2u23 autocran1.3K conda_forge26 c2d4u

Dependencies

Declared dependencies
16 external dependencies (excludes base and recommended)
Depends (0)
none
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
1direct
0indirect

Code & Tests

People & History

People (0)

Author records are not tracked yet for this package.

Listed in earlier versions (1)
no longer listed · 0.1.3 to 0.2.4
Package Timeline

7 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
  • R
    R 4.2.0 released · 2022-04-22
  • 0.2.4Latest
    2021-05-31 · current release · diff ↗
  • unarchivedReturned to CRAN
    2021-05-31
  • R
    R 4.1.0 released · 2021-05-18
  • archivedRemoved from CRAN
    2021-04-28
    check problems were not corrected in time Suggests: packages not used conditionally
  • 0.2.0
    2021-03-21 · diff ↗
  • 0.1.7
    2021-01-06 · diff ↗
  • 0.1.6
    2020-12-12 · diff ↗
  • 0.1.5
    2020-07-26 · diff ↗
  • 0.1.4
    2020-05-11 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 0.1.3
    2019-08-01
Show 1 earlier events
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2019-08-01
Total releases
7 / 7 yrs
License
GPL-3 OSI
Download size
765 KB
Installed size
not tracked yet
With dependencies
not tracked yet
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ClustImpute")

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ClustImpute version 0.2.4 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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