Learn R Programming
⚠️There's a newer version (6.1) of this package.Take me there.

mclust (version 5.4.10)

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.

Copy Link

Version

Install

install.packages('mclust')

Monthly Downloads

74,004

Version

5.4.10

License

GPL (>= 2)

Maintainer

Luca Scrucca

Last Published

May 20th, 2022

Functions in mclust (5.4.10)

GvHD

GvHD Dataset
MclustDRsubsel

Subset selection for GMMDR directions based on BIC
MclustDA

MclustDA discriminant analysis
EuroUnemployment

Unemployment data for European countries in 2014
BrierScore

Brier score to assess the accuracy of probabilistic predictions
MclustSSC

MclustSSC semi-supervised classification
MclustBootstrap

Resampling-based Inference for Gaussian finite mixture models
Mclust

Model-Based Clustering
MclustDR

Dimension reduction for model-based clustering and classification
clPairs

Pairwise Scatter Plots showing Classification
Baudry_etal_2010_JCGS_examples

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

Swiss banknotes data
clustCombi-internal

Internal clustCombi functions
classPriorProbs

Estimation of class prior probabilities by EM algorithm
chevron

Simulated minefield data
densityMclust.diagnostic

Diagnostic plots for mclustDensity estimation
cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
clustCombi

Combining Gaussian Mixture Components for Clustering
acidity

Acidity data
cdens

Component Density for Parameterized MVN Mixture Models
adjustedRandIndex

Adjusted Rand Index
covw

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

Classification error
cdensE

Component Density for a Parameterized MVN Mixture Model
diabetes

Diabetes Data (flawed)
dens

Density for Parameterized MVN Mixtures
combiTree

Tree structure obtained from combining mixture components
icl

ICL for an estimated Gaussian Mixture Model
decomp2sigma

Convert mixture component covariances to matrix form
em

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

Default conjugate prior for Gaussian mixtures
crimcoords

Discriminant coordinates data projection
coordProj

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

Set control values for use with the EM algorithm
clustCombiOptim

Optimal number of clusters obtained by combining mixture components
hcE

Model-based Hierarchical Clustering
hc

Model-based Agglomerative Hierarchical Clustering
bic

BIC for Parameterized Gaussian Mixture Models
densityMclust

Density Estimation via Model-Based Clustering
majorityVote

Majority vote
mclustICL

ICL Criterion for Model-Based Clustering
dmvnorm

Density of multivariate Gaussian distribution
surfacePlot

Density or uncertainty surface for bivariate mixtures
plot.mclustICL

ICL Plot for Model-Based Clustering
predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling
nVarParams

Number of Variance Parameters in Gaussian Mixture Models
partconv

Numeric Encoding of a Partitioning
errorBars

Draw error bars on a plot
mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components
logLik.MclustDA

Log-Likelihood of a MclustDA object
dupPartition

Partition the data by grouping together duplicated data
me.weighted

EM algorithm with weights starting with M-step for parameterized MVN mixture models
estep

E-step for parameterized Gaussian mixture models.
mvnX

Univariate or Multivariate Normal Fit
mapClass

Correspondence between classifications
map

Classification given Probabilities
imputeData

Missing data imputation via the mix package
me

EM algorithm starting with M-step for parameterized MVN mixture models
nMclustParams

Number of Estimated Parameters in Gaussian Mixture Models
plot.clustCombi

Plot Combined Clusterings Results
plot.densityMclust

Plots for Mixture-Based Density Estimate
thyroid

UCI Thyroid Gland Data
summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits
summary.MclustSSC

Summarizing semi-supervised classification model based on Gaussian finite mixtures
summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
summary.mclustBIC

Summary function for model-based clustering via BIC
imputePairs

Pairwise Scatter Plots showing Missing Data Imputations
mclustBIC

BIC for Model-Based Clustering
emE

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

Plot Entropy Plots
logLik.Mclust

Log-Likelihood of a Mclust object
combMat

Combining Matrix
mclustBICupdate

Update BIC values for parameterized Gaussian mixture models
meE

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

Random hierarchical structure
hclass

Classifications from Hierarchical Agglomeration
mclust2Dplot

Plot two-dimensional data modelled by an MVN mixture
mclustVariance

Template for variance specification for parameterized Gaussian mixture models
plot.MclustBootstrap

Plot of bootstrap distributions for mixture model parameters
mclustModelNames

MCLUST Model Names
mclust1Dplot

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

M-step for parameterized Gaussian mixture models
plot.MclustSSC

Plotting method for MclustSSC semi-supervised classification
mclust-package

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

Plotting method for dimension reduction for model-based clustering and classification
combiPlot

Plot Classifications Corresponding to Successive Combined Solutions
cross

Simulated Cross Data
gmmhd

Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
cvMclustDA

MclustDA cross-validation
estepE

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

Plotting method for MclustDA discriminant analysis
simE

Simulate from a Parameterized MVN Mixture Model
sim

Simulate from Parameterized MVN Mixture Models
predict.MclustSSC

Classification of multivariate observations by semi-supervised Gaussian finite mixtures
hypvol

Aproximate Hypervolume for Multivariate Data
hdrlevels

Highest Density Region (HDR) Levels
predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling
mclust-deprecated

Deprecated Functions in mclust package
mclust.options

Default values for use with MCLUST package
partuniq

Classifies Data According to Unique Observations
mclustModel

Best model based on BIC
mclustLoglik

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

Internal MCLUST functions
wdbc

UCI Wisconsin Diagnostic Breast Cancer Data
wreath

Data Simulated from a 14-Component Mixture
predict.MclustDR

Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling
uncerPlot

Uncertainty Plot for Model-Based Clustering
mstepE

M-step for a parameterized Gaussian mixture model
mvn

Univariate or Multivariate Normal Fit
plot.Mclust

Plotting method for Mclust model-based clustering
priorControl

Conjugate Prior for Gaussian Mixtures.
randProj

Random projections of multidimensional data modeled by an MVN mixture
unmap

Indicator Variables given Classification
plot.mclustBIC

BIC Plot for Model-Based Clustering
randomOrthogonalMatrix

Random orthogonal matrix
sigma2decomp

Convert mixture component covariances to decomposition form.
plot.hc

Dendrograms for Model-based Agglomerative Hierarchical Clustering
summary.MclustDR

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

Summarizing discriminant analysis based on Gaussian finite mixture modeling