This package is considered a duplicate. The official version of this package is found at:https://luca-scr.r-universe.dev/mclust

Package: mclust 6.1.2

Luca Scrucca

mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

Authors:Chris Fraley [aut], Adrian E. Raftery [aut], Luca Scrucca [aut, cre], Thomas Brendan Murphy [ctb], Michael Fop [ctb]

mclust_6.1.2.tar.gz
mclust_6.1.2.tar.gz(r-4.7-arm64)mclust_6.1.2.tar.gz(r-4.7-x86_64)mclust_6.1.2.tar.gz(r-4.6-arm64)mclust_6.1.2.tar.gz(r-4.6-x86_64)
mclust_6.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mclust/json (API)
NEWS

# Install 'mclust' in R:

install.packages('mclust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mclust-org/mclust/issues

Pkgdown/docs site:https://mclust-org.github.io

Uses libs:

openblas– Optimized BLAS

Datasets:

acidity - Acidity data
banknote - Swiss banknotes data
chevron - Simulated minefield data
cross - Simulated Cross Data
diabetes - Diabetes Data
EuroUnemployment - Unemployment data for European countries in 2014
ex4.1 - Simulated Example Datasets From Baudry et al.
ex4.2 - Simulated Example Datasets From Baudry et al.
ex4.3 - Simulated Example Datasets From Baudry et al.
ex4.4.1 - Simulated Example Datasets From Baudry et al.
ex4.4.2 - Simulated Example Datasets From Baudry et al.
GvHD.control - GvHD Dataset
GvHD.pos - GvHD Dataset
Test1D - Simulated Example Datasets From Baudry et al.
thyroid - UCI Thyroid Gland Data
wdbc - UCI Wisconsin Diagnostic Breast Cancer Data
wreath - Data Simulated from a 14-Component Mixture

On CRAN:

openblas

12.43 score 20 stars 635 packages 7.8k scripts 91k downloads 297 mentions 281 exports 0 dependencies

Last updated from:5b4f493715. Checks:6 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	172
linux-devel-x86_64	OK	162
source / vignettes	OK	251
linux-release-arm64	OK	182
linux-release-x86_64	OK	166
wasm-release	OK	130

Exports:adjustedRandIndex as.densityMclust as.densityMclust.default as.densityMclust.Mclust as.hclust.hc as.Mclust as.Mclust.default as.Mclust.densityMclust bic bicEMtrain BrierScore cdens cdensE cdensEEE cdensEEI cdensEEV cdensEII cdensEVE cdensEVI cdensEVV cdensV cdensVEE cdensVEI cdensVEV cdensVII cdensVVE cdensVVI cdensVVV cdensX cdensXII cdensXXI cdensXXX cdfMclust checkModelName classError classPriorProbs clPairs clPairsLegend clustCombi clustCombiOptim combiPlot combiTree combMat coordProj count covw crimcoords cv.MclustDA cv1EMtrain cvMclustDA decomp2sigma defaultPrior dens densityMclust densityMclust.diagnostic dmvnorm dupPartition em emControl emE emEEE emEEI emEEV emEII emEVE emEVI emEVV emV emVEE emVEI emVEV emVII emVVE emVVI emVVV emX emXII emXXI emXXX entPlot errorBars estep estepE estepEEE estepEEI estepEEV estepEII estepEVE estepEVI estepEVV estepV estepVEE estepVEI estepVEV estepVII estepVVE estepVVI estepVVV getParameters.MclustDA gmmhd gmmhdClassify gmmhdClusterCores hc hcE hcEEE hcEII hclass hcRandomPairs hcV hcVII hcVVV hdrlevels hypvol icl imputeData imputePairs logLik.Mclust logLik.MclustDA logsumexp majorityVote map mapClass matchCluster Mclust mclust.options mclust1Dplot mclust2Dplot mclustBIC mclustBICupdate MclustBootstrap mclustBootstrapLRT MclustDA MclustDR MclustDRrecoverdir MclustDRsubsel MclustDRsubsel_classif MclustDRsubsel_cluster MclustDRsubsel1cycle mclustICL mclustLoglik mclustModel mclustModelNames MclustSSC mclustVariance me me.weighted meE meEEE meEEI meEEV meEII meEVE meEVI meEVV meV meVEE meVEI meVEV meVII meVVE meVVI meVVV meX meXII meXXI meXXX mstep mstepE mstepEEE mstepEEI mstepEEV mstepEII mstepEVE mstepEVI mstepEVV mstepV mstepVEE mstepVEI mstepVEV mstepVII mstepVVE mstepVVI mstepVVV mvn mvn2plot mvnX mvnXII mvnXXI mvnXXX nMclustParams nVarParams partconv partuniq pickBIC plot.clustCombi plot.crimcoords plot.densityMclust plot.gmmhd plot.hc plot.Mclust plot.mclustBIC plot.MclustBootstrap plot.mclustBootstrapLRT plot.MclustDA plot.MclustDR plot.mclustICL plot.MclustSSC plotDensityMclust1 plotDensityMclust2 plotDensityMclustd plotEvalues.MclustDR predict.densityMclust predict.Mclust predict.MclustDA predict.MclustDR predict.MclustSSC predict2D.MclustDR print.clustCombi print.crimcoords print.gmmhd print.hc print.Mclust print.mclustBIC print.MclustBootstrap print.mclustBootstrapLRT print.MclustDA print.MclustDR print.MclustDRsubsel print.mclustICL print.mclustLoglik print.MclustSSC print.summary.clustCombi print.summary.crimcoords print.summary.gmmhd print.summary.Mclust print.summary.MclustBootstrap print.summary.MclustDA print.summary.MclustDR print.summary.mclustICL print.summary.MclustSSC priorControl projpar.MclustDR quantileMclust randomOrthogonalMatrix randomPairs randProj sigma2decomp sim simE simEEE simEEI simEEV simEII simEVE simEVI simEVV simV simVEE simVEI simVEV simVII simVVE simVVI simVVV softmax summary.clustCombi summary.crimcoords summary.gmmhd summary.Mclust summary.mclustBIC summary.MclustBootstrap summary.MclustDA summary.MclustDR summary.MclustDRsubsel summary.mclustICL summary.MclustSSC summaryMclustBIC summaryMclustBICn surfacePlot uncerPlot unmap

Dependencies:

A quick tour of mclust

Luca Scrucca

Rendered frommclust.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2025-10-31
Started: 2015-04-01

Citation

Readme and manuals

Help Manual

Help page	Topics
Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation	mclust-package mclust
Acidity data	acidity
Adjusted Rand Index	adjustedRandIndex
Swiss banknotes data	banknote
Simulated Example Datasets From Baudry et al. (2010)	Baudry_etal_2010_JCGS_examples ex4.1 ex4.2 ex4.3 ex4.4.1 ex4.4.2 Test1D
BIC for Parameterized Gaussian Mixture Models	bic
Brier score to assess the accuracy of probabilistic predictions	BrierScore
Component Density for Parameterized MVN Mixture Models	cdens
Component Density for a Parameterized MVN Mixture Model	cdensE cdensEEE cdensEEI cdensEEV cdensEII cdensEVE cdensEVI cdensEVV cdensV cdensVEE cdensVEI cdensVEV cdensVII cdensVVE cdensVVI cdensVVV cdensX cdensXII cdensXXI cdensXXX
Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution	cdfMclust quantileMclust
Simulated minefield data	chevron
Classification error	classError
Estimation of class prior probabilities by EM algorithm	classPriorProbs
Pairwise Scatter Plots showing Classification	clPairs clPairsLegend
Combining Gaussian Mixture Components for Clustering	clustCombi print.clustCombi print.summary.clustCombi summary.clustCombi
Optimal number of clusters obtained by combining mixture components	clustCombiOptim
Plot Classifications Corresponding to Successive Combined Solutions	combiPlot
Tree structure obtained from combining mixture components	combiTree
Combining Matrix	combMat
Coordinate projections of multidimensional data modeled by an MVN mixture.	coordProj
Weighted means, covariance and scattering matrices conditioning on a weighted matrix	covw
Discriminant coordinates data projection	crimcoords plot.crimcoords print.crimcoords print.summary.crimcoords summary.crimcoords
Simulated Cross Data	cross
MclustDA cross-validation	cvMclustDA
Convert mixture component covariances to matrix form	decomp2sigma
Default conjugate prior for Gaussian mixtures	defaultPrior
Density for Parameterized MVN Mixtures	dens
Density Estimation via Model-Based Clustering	densityMclust
Diagnostic plots for 'mclustDensity' estimation	densityMclust.diagnostic
Diabetes Data (flawed)	diabetes
Density of multivariate Gaussian distribution	dmvnorm
Partition the data by grouping together duplicated data	dupPartition
EM algorithm starting with E-step for parameterized Gaussian mixture models	em
Set control values for use with the EM algorithm	emControl
EM algorithm starting with E-step for a parameterized Gaussian mixture model	emE emEEE emEEI emEEV emEII emEVE emEVI emEVV emV emVEE emVEI emVEV emVII emVVE emVVI emVVV emX emXII emXXI emXXX
Plot Entropy Plots	entPlot
Draw error bars on a plot	errorBars
E-step for parameterized Gaussian mixture models.	estep
E-step in the EM algorithm for a parameterized Gaussian mixture model.	estepE estepEEE estepEEI estepEEV estepEII estepEVE estepEVI estepEVV estepV estepVEE estepVEI estepVEV estepVII estepVVE estepVVI estepVVV
Unemployment data for European countries in 2014	EuroUnemployment
Identifying Connected Components in Gaussian Finite Mixture Models for Clustering	gmmhd gmmhdClassify gmmhdClusterCores plot.gmmhd print.gmmhd print.summary.gmmhd summary.gmmhd
GvHD Dataset	GvHD GvHD.control GvHD.pos
Model-based Agglomerative Hierarchical Clustering	as.hclust.hc hc print.hc
Model-based Hierarchical Clustering	hcE hcEEE hcEII hcV hcVII hcVVV
Classifications from Hierarchical Agglomeration	hclass
Random hierarchical structure	hcRandomPairs randomPairs
Highest Density Region (HDR) Levels	hdrlevels
Aproximate Hypervolume for Multivariate Data	hypvol
ICL for an estimated Gaussian Mixture Model	icl
Missing data imputation via the 'mix' package	imputeData matchCluster
Pairwise Scatter Plots showing Missing Data Imputations	imputePairs
Log-Likelihood of a 'Mclust' object	logLik.Mclust
Log-Likelihood of a 'MclustDA' object	logLik.MclustDA
Log sum of exponentials	logsumexp
Majority vote	majorityVote
Classification given Probabilities	map
Correspondence between classifications	mapClass
Model-Based Clustering	Mclust print.Mclust
Deprecated Functions in mclust package	bicEMtrain cv.MclustDA cv1EMtrain
Default values for use with MCLUST package	mclust.options
Plot one-dimensional data modeled by an MVN mixture.	mclust1Dplot
Plot two-dimensional data modelled by an MVN mixture	mclust2Dplot
BIC for Model-Based Clustering	EMclust mclustBIC print.mclustBIC
Update BIC values for parameterized Gaussian mixture models	mclustBICupdate
Resampling-based Inference for Gaussian finite mixture models	MclustBootstrap print.MclustBootstrap
Bootstrap Likelihood Ratio Test for the Number of Mixture Components	mclustBootstrapLRT plot.mclustBootstrapLRT print.mclustBootstrapLRT
MclustDA discriminant analysis	MclustDA print.MclustDA
Dimension reduction for model-based clustering and classification	MclustDR print.MclustDR
Subset selection for GMMDR directions based on BIC	MclustDRrecoverdir MclustDRsubsel MclustDRsubsel1cycle MclustDRsubsel_classif MclustDRsubsel_cluster print.MclustDRsubsel summary.MclustDRsubsel
ICL Criterion for Model-Based Clustering	mclustICL print.mclustICL print.summary.mclustICL summary.mclustICL
Log-likelihood from a table of BIC values for parameterized Gaussian mixture models	mclustLoglik print.mclustLoglik
Best model based on BIC	mclustModel
MCLUST Model Names	mclustModelNames
MclustSSC semi-supervised classification	MclustSSC print.MclustSSC
Template for variance specification for parameterized Gaussian mixture models	mclustVariance
EM algorithm starting with M-step for parameterized MVN mixture models	me
EM algorithm with weights starting with M-step for parameterized Gaussian mixture models	me.weighted
EM algorithm starting with M-step for a parameterized Gaussian mixture model	meE meEEE meEEI meEEV meEII meEVE meEVI meEVV meV meVEE meVEI meVEV meVII meVVE meVVI meVVV meX meXII meXXI meXXX
M-step for parameterized Gaussian mixture models	mstep
M-step for a parameterized Gaussian mixture model	mstepE mstepEEE mstepEEI mstepEEV mstepEII mstepEVE mstepEVI mstepEVV mstepV mstepVEE mstepVEI mstepVEV mstepVII mstepVVE mstepVVI mstepVVV
Univariate or Multivariate Normal Fit	mvn
Univariate or Multivariate Normal Fit	mvnX mvnXII mvnXXI mvnXXX
Number of Estimated Parameters in Gaussian Mixture Models	nMclustParams
Number of Variance Parameters in Gaussian Mixture Models	nVarParams
Numeric Encoding of a Partitioning	partconv
Classifies Data According to Unique Observations	partuniq
Plot Combined Clusterings Results	plot.clustCombi
Plots for Mixture-Based Density Estimate	plot.densityMclust plotDensityMclust1 plotDensityMclust2 plotDensityMclustd
Dendrograms for Model-based Agglomerative Hierarchical Clustering	plot.hc
Plotting method for Mclust model-based clustering	plot.Mclust
BIC Plot for Model-Based Clustering	plot.mclustBIC
Plot of bootstrap distributions for mixture model parameters	plot.MclustBootstrap
Plotting method for MclustDA discriminant analysis	plot.MclustDA
Plotting method for dimension reduction for model-based clustering and classification	plot.MclustDR plotEvalues.MclustDR
ICL Plot for Model-Based Clustering	plot.mclustICL
Plotting method for MclustSSC semi-supervised classification	plot.MclustSSC
Density estimate of multivariate observations by Gaussian finite mixture modeling	predict.densityMclust
Cluster multivariate observations by Gaussian finite mixture modeling	predict.Mclust
Classify multivariate observations by Gaussian finite mixture modeling	predict.MclustDA
Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling	predict.MclustDR predict2D.MclustDR
Classification of multivariate observations by semi-supervised Gaussian finite mixtures	predict.MclustSSC
Conjugate Prior for Gaussian Mixtures.	priorControl
Random orthogonal matrix	randomOrthogonalMatrix
Random projections of multidimensional data modeled by an MVN mixture	randProj
Convert mixture component covariances to decomposition form.	sigma2decomp
Simulate from Parameterized MVN Mixture Models	sim
Simulate from a Parameterized MVN Mixture Model	simE simEEE simEEI simEEV simEII simEVE simEVI simEVV simV simVEE simVEI simVEV simVII simVVE simVVI simVVV
Softmax function	softmax
Summarizing Gaussian Finite Mixture Model Fits	print.summary.Mclust summary.Mclust
Summary function for model-based clustering via BIC	print.summary.mclustBIC printSummaryMclustBIC printSummaryMclustBICn summary.mclustBIC summaryMclustBIC summaryMclustBICn
Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models	print.summary.MclustBootstrap summary.MclustBootstrap
Summarizing discriminant analysis based on Gaussian finite mixture modeling	print.summary.MclustDA summary.MclustDA
Summarizing dimension reduction method for model-based clustering and classification	print.summary.MclustDR summary.MclustDR
Summarizing semi-supervised classification model based on Gaussian finite mixtures	print.summary.MclustSSC summary.MclustSSC
Density or uncertainty surface for bivariate mixtures	surfacePlot
UCI Thyroid Gland Data	thyroid
Uncertainty Plot for Model-Based Clustering	uncerPlot
Indicator Variables given Classification	unmap
UCI Wisconsin Diagnostic Breast Cancer Data	wdbc
Data Simulated from a 14-Component Mixture	wreath