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mclust (version 6.1.3)

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

Description

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.

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Version

Install

install.packages('mclust')

Monthly Downloads

82,415

Version

6.1.3

License

GPL (>= 2)

Maintainer

Luca Scrucca

Last Published

July 5th, 2026

Functions in mclust (6.1.3)

adjustedRandIndex

Adjusted Rand Index
banknote

Swiss banknotes data
chevron

Simulated minefield data
acidity

Acidity data
classError

Classification error
cdensE

Component Density for a Parameterized MVN Mixture Model
clPairs

Pairwise Scatter Plots showing Classification
cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
covw

Weighted means, covariance and scattering matrices conditioning on a weighted matrix
clustCombi

Combining Gaussian Mixture Components for Clustering
bic

BIC for Parameterized Gaussian Mixture Models
combiTree

Tree structure obtained from combining mixture components
coordProj

Coordinate projections of multidimensional data modeled by an MVN mixture.
diabetes

Diabetes Data (flawed)
densityMclust.diagnostic

Diagnostic plots for mclustDensity estimation
dmvnorm

Density of multivariate Gaussian distribution
combMat

Combining Matrix
defaultPrior

Default conjugate prior for Gaussian mixtures
dupPartition

Partition the data by grouping together duplicated data
combiPlot

Plot Classifications Corresponding to Successive Combined Solutions
decomp2sigma

Convert mixture component covariances to matrix form
clustCombiOptim

Optimal number of clusters obtained by combining mixture components
cvMclustDA

MclustDA cross-validation
cross

Simulated Cross Data
clustCombi-internal

Internal clustCombi functions
classPriorProbs

Estimation of class prior probabilities by EM algorithm
densityMclust

Density Estimation via Model-Based Clustering
crimcoords

Discriminant coordinates data projection
dens

Density for Parameterized MVN Mixtures
hc

Model-based Agglomerative Hierarchical Clustering
hcE

Model-based Hierarchical Clustering
em

EM algorithm starting with E-step for parameterized Gaussian mixture models
emControl

Set control values for use with the EM algorithm
hcRandomPairs

Random hierarchical structure
entPlot

Plot Entropy Plots
emE

EM algorithm starting with E-step for a parameterized Gaussian mixture model
estepE

E-step in the EM algorithm for a parameterized Gaussian mixture model.
icl

ICL for an estimated Gaussian Mixture Model
imputeData

Missing data imputation via the mix package
gmmhd

Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
errorBars

Draw error bars on a plot
estep

E-step for parameterized Gaussian mixture models.
hdrlevels

Highest Density Region (HDR) Levels
mclust-deprecated

Deprecated Functions in mclust package
majorityVote

Majority vote
logsumexp

Log sum of exponentials
imputePairs

Pairwise Scatter Plots showing Missing Data Imputations
logLik.Mclust

Log-Likelihood of a Mclust object
mclustBIC

BIC for Model-Based Clustering
mclust2Dplot

Plot two-dimensional data modelled by an MVN mixture
hclass

Classifications from Hierarchical Agglomeration
mapClass

Correspondence between classifications
mclust.options

Default values for use with MCLUST package
map

Classification given Probabilities
logLik.MclustDA

Log-Likelihood of a MclustDA object
hypvol

Approximate Hypervolume for Multivariate Data
mclust-internal

Internal MCLUST functions
mclustBICupdate

Update BIC values for parameterized Gaussian mixture models
mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components
mclust-package

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

Number of Estimated Parameters in Gaussian Mixture Models
mvnX

Univariate or Multivariate Normal Fit
mclustModel

Best model based on BIC
mvn

Univariate or Multivariate Normal Fit
mclustModelNames

MCLUST Model Names
mstepE

M-step for a parameterized Gaussian mixture model
mclust1Dplot

Plot one-dimensional data modeled by an MVN mixture.
mclustLoglik

Log-likelihood from a table of BIC values for parameterized Gaussian mixture models
mstep

M-step for parameterized Gaussian mixture models
predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling
predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling
mclustICL

ICL Criterion for Model-Based Clustering
nVarParams

Number of Variance Parameters in Gaussian Mixture Models
plot.MclustSSC

Plotting method for MclustSSC semi-supervised classification
me.weighted

EM algorithm with weights starting with M-step for parameterized Gaussian mixture models
partconv

Numeric Encoding of a Partitioning
meE

EM algorithm starting with M-step for a parameterized Gaussian mixture model
mclustVariance

Template for variance specification for parameterized Gaussian mixture models
partuniq

Classifies Data According to Unique Observations
randProj

Random projections of multidimensional data modeled by an MVN mixture
simulate.Mclust

Simulate from Gaussian mixture models
predict.MclustDR

Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
plot.MclustDR

Plotting method for dimension reduction for model-based clustering and classification
predict.MclustSSC

Classification of multivariate observations by semi-supervised Gaussian finite mixtures
plot.MclustDA

Plotting method for MclustDA discriminant analysis
simE

Simulate from a Parameterized MVN Mixture Model
me

EM algorithm starting with M-step for parameterized MVN mixture models
plot.clustCombi

Plot Combined Clusterings Results
softmax

Softmax function
summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits
unmap

Indicator Variables given Classification
wdbc

UCI Wisconsin Diagnostic Breast Cancer Data
randomOrthogonalMatrix

Random orthogonal matrix
summary.mclustBIC

Summary function for model-based clustering via BIC
surfacePlot

Density or uncertainty surface for bivariate mixtures
priorControl

Conjugate Prior for Gaussian Mixtures.
wreath

Data Simulated from a 14-Component Mixture
plot.hc

Dendrograms for Model-based Agglomerative Hierarchical Clustering
sim

Simulate from Parameterized MVN Mixture Models
sigma2decomp

Convert mixture component covariances to decomposition form.
predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling
summary.MclustDA

Summarizing discriminant analysis based on Gaussian finite mixture modeling
plot.MclustBootstrap

Plot of bootstrap distributions for mixture model parameters
plot.Mclust

Plotting method for Mclust model-based clustering
plot.mclustBIC

BIC Plot for Model-Based Clustering
summary.MclustDR

Summarizing dimension reduction method for model-based clustering and classification
summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
plot.densityMclust

Plots for Mixture-Based Density Estimate
uncerPlot

Uncertainty Plot for Model-Based Clustering
plot.mclustICL

ICL Plot for Model-Based Clustering
summary.MclustSSC

Summarizing semi-supervised classification model based on Gaussian finite mixtures
thyroid

UCI Thyroid Gland Data
Mclust

Model-Based Clustering
EuroUnemployment

Unemployment data for European countries in 2014
MclustDR

Dimension reduction for model-based clustering and classification
MclustDRsubsel

Subset selection for GMMDR directions based on BIC
MclustDA

MclustDA discriminant analysis
Baudry_etal_2010_JCGS_examples

Simulated Example Datasets From Baudry et al. (2010)
BrierScore

Brier score to assess the accuracy of probabilistic predictions
MclustBootstrap

Resampling-based Inference for Gaussian finite mixture models
GvHD

GvHD Dataset
cdens

Component Density for Parameterized MVN Mixture Models
MclustSSC

MclustSSC semi-supervised classification