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K Quantiles Medoids (KQM) Clustering

0packages depend
1.9Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

K Quantiles Medoids (KQM) clustering applies quantiles to divide data of each dimension into K mean intervals. Combining quantiles of all the dimensions of the data and fully permuting quantiles on each dimension is the strategy to determine a pool of candidate initial cluster centers. To find the best initial cluster centers from the pool of candidate initial cluster centers, two methods based on quantile strategy and PAM strategy respectively are proposed. During a clustering process, medoids of clusters are used to update cluster centers in each iteration. Comparison between KQM and the method of randomly selecting initial cluster centers shows that KQM is almost always getting clustering results with smaller total sum squares of distances.

Install

Health

CRAN checks
13OK
Slowest check: 52 s · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.1.1
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
5includes a package overview page
Examples that run
100%5 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
60%

Downloads

1.9K
CRAN downloads in the past year
Rank #23,710 · ~5/day · ~158/mo
Daily download trend is not available in this view yet.
25130 days
53790 days
1.9K1 year
Compare downloads with other packages →
Also on64 r2u4 autocran

Dependencies

Declared dependencies
1 external dependency (excludes base and recommended)

Installing KQM adds 1 package (1 with compiled code, 236 KB of source tarballs). Heaviest: gtools 236 KB.

Depends (4)
methodsMASSgtoolscluster
Imports (0)
none
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (4)
Author, Maintainer since 1.1.1 (2025)
Contributor
Contributor
Contributor
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 1.1.1Latest
    2025-10-16 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-10-16
Total releases
1 / 1 yrs
License
GPL-2 OSI
Download size
5.3 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("KQM")
Yang, Y., Ebrahimi, N., Rubin, Y., & Zhang, J. (2025). KQM: K Quantiles Medoids (KQM) Clustering (Version 1.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.KQM

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 KQM version 1.1.1 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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