cclustr: Consensus Clustering Methods for Multiple Imputed Data

Provides tools for performing consensus clustering on multiple imputed datasets. The package supports a range of clustering algorithms across imputations, including hierarchical methods (e.g., Ward, single, complete, average) and partition-based approaches such as k-means, k-medoids (PAM), fuzzy clustering, model-based clustering ('mclust'), and methods for mixed or categorical data (k-modes and k-prototypes). A co-assignment matrix is constructed to quantify agreement between partitions, and consensus solutions are derived via hierarchical clustering applied to the resulting dissimilarity matrix. Additional functions are provided for validation and visualization of clustering results, facilitating robust analysis in the presence of missing data. Consensus clustering framework is based on Monti et al. (2003) <doi:10.1023/A:1023949509487>, rank aggregation methods follow Pihur et al. (2007) <doi:10.1093/bioinformatics/btm158>, and the PAC (Proportion of Ambiguous Clustering) metric is based on Senbabaoglu et al. (2014) <doi:10.1038/srep06207>.

Version:	0.1.1
Depends:	R (≥ 4.0)
Imports:	cluster, e1071, fpc, graphics, stats, viridisLite, klaR, clustMixType, proxy, mclust
Suggests:	knitr, mice, mlbench, rmarkdown, spelling, testthat (≥ 3.0.0), utils
Published:	2026-05-18
DOI:	10.32614/CRAN.package.cclustr
Author:	Anhuar Duran Mendoza [aut], Andres Montenegro Lemus [aut, cre], Mario Pacheco Lopez [aut]
Maintainer:	Andres Montenegro Lemus <andresfemole at gmail.com>
BugReports:	https://github.com/andrews06ml/cclustr/issues
License:	MIT + file LICENSE
URL:	https://github.com/andrews06ml/cclustr
NeedsCompilation:	no
Language:	en-US
Materials:	NEWS
CRAN checks:	cclustr results

Documentation:

Reference manual:	cclustr.html , cclustr.pdf
Vignettes:	Consensus Clustering with Multiple Imputed Data using cclustr (source, R code)

Downloads:

Package source:	cclustr_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: cclustr_0.1.1.zip, r-oldrel: cclustr_0.1.1.zip
macOS binaries:	r-release (arm64): cclustr_0.1.1.tgz, r-oldrel (arm64): cclustr_0.1.1.tgz, r-release (x86_64): cclustr_0.1.1.tgz, r-oldrel (x86_64): cclustr_0.1.1.tgz

Linking:

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