mixture: Mixture Models for Clustering and Classification

An implementation of 14 parsimonious mixture models for model-based clustering or model-based classification. Gaussian, Student's t, generalized hyperbolic, variance-gamma or skew-t mixtures are available. All approaches work with missing data. Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>, Browne and McNicholas (2014) <doi:10.1007/s11634-013-0139-1>, Browne and McNicholas (2015) <doi:10.1002/cjs.11246>.

Version:	2.2.0
Depends:	R (≥ 3.5.0), lattice (≥ 0.20)
Imports:	Rcpp (≥ 1.0.2), methods
LinkingTo:	Rcpp, RcppArmadillo, BH, RcppGSL
Published:	2025-12-18
DOI:	10.32614/CRAN.package.mixture
Author:	Nik Pocuca [aut], Ryan P. Browne [aut], Paul D. McNicholas [aut, cre], Alexa A. Sochaniwsky [aut]
Maintainer:	Paul D. McNicholas <mcnicholas at math.mcmaster.ca>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
SystemRequirements:	GNU GSL
Materials:	ChangeLog
In views:	Cluster, MissingData
CRAN checks:	mixture results

Documentation:

Reference manual:

mixture.html , mixture.pdf

Downloads:

Package source:	mixture_2.2.0.tar.gz
Windows binaries:	r-devel: mixture_2.2.0.zip, r-release: mixture_2.2.0.zip, r-oldrel: mixture_2.2.0.zip
macOS binaries:	r-release (arm64): mixture_2.2.0.tgz, r-oldrel (arm64): mixture_2.2.0.tgz, r-release (x86_64): mixture_2.2.0.tgz, r-oldrel (x86_64): mixture_2.2.0.tgz
Old sources:	mixture archive

Reverse dependencies:

Reverse imports:

Compositional, CompositionalClust, ContaminatedMixt, MixGHD, oclust, outlierMBC

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mixture to link to this page.