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

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Documentation for package ‘mclust’ version 6.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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A B C D E G H I L M N P Q R S T U W

mclust-package

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

-- A --

acidity	Acidity data
adjustedRandIndex	Adjusted Rand Index
as.hclust.hc	Model-based Agglomerative Hierarchical Clustering

-- B --

banknote	Swiss banknotes data
Baudry_etal_2010_JCGS_examples	Simulated Example Datasets From Baudry et al. (2010)
bic	BIC for Parameterized Gaussian Mixture Models
bicEMtrain	Deprecated Functions in mclust package
BrierScore	Brier score to assess the accuracy of probabilistic predictions

-- C --

cdens	Component Density for Parameterized MVN Mixture Models
cdensE	Component Density for a Parameterized MVN Mixture Model
cdensEEE	Component Density for a Parameterized MVN Mixture Model
cdensEEI	Component Density for a Parameterized MVN Mixture Model
cdensEEV	Component Density for a Parameterized MVN Mixture Model
cdensEII	Component Density for a Parameterized MVN Mixture Model
cdensEVE	Component Density for a Parameterized MVN Mixture Model
cdensEVI	Component Density for a Parameterized MVN Mixture Model
cdensEVV	Component Density for a Parameterized MVN Mixture Model
cdensV	Component Density for a Parameterized MVN Mixture Model
cdensVEE	Component Density for a Parameterized MVN Mixture Model
cdensVEI	Component Density for a Parameterized MVN Mixture Model
cdensVEV	Component Density for a Parameterized MVN Mixture Model
cdensVII	Component Density for a Parameterized MVN Mixture Model
cdensVVE	Component Density for a Parameterized MVN Mixture Model
cdensVVI	Component Density for a Parameterized MVN Mixture Model
cdensVVV	Component Density for a Parameterized MVN Mixture Model
cdensX	Component Density for a Parameterized MVN Mixture Model
cdensXII	Component Density for a Parameterized MVN Mixture Model
cdensXXI	Component Density for a Parameterized MVN Mixture Model
cdensXXX	Component Density for a Parameterized MVN Mixture Model
cdfMclust	Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
chevron	Simulated minefield data
classError	Classification error
classPriorProbs	Estimation of class prior probabilities by EM algorithm
clPairs	Pairwise Scatter Plots showing Classification
clPairsLegend	Pairwise Scatter Plots showing Classification
clustCombi	Combining Gaussian Mixture Components for Clustering
clustCombiOptim	Optimal number of clusters obtained by combining mixture components
combiPlot	Plot Classifications Corresponding to Successive Combined Solutions
combiTree	Tree structure obtained from combining mixture components
combMat	Combining Matrix
coordProj	Coordinate projections of multidimensional data modeled by an MVN mixture.
covw	Weighted means, covariance and scattering matrices conditioning on a weighted matrix
crimcoords	Discriminant coordinates data projection
cross	Simulated Cross Data
cv.MclustDA	Deprecated Functions in mclust package
cv1EMtrain	Deprecated Functions in mclust package
cvMclustDA	MclustDA cross-validation

-- D --

decomp2sigma	Convert mixture component covariances to matrix form
defaultPrior	Default conjugate prior for Gaussian mixtures
dens	Density for Parameterized MVN Mixtures
densityMclust	Density Estimation via Model-Based Clustering
densityMclust.diagnostic	Diagnostic plots for 'mclustDensity' estimation
diabetes	Diabetes Data (flawed)
dmvnorm	Density of multivariate Gaussian distribution
dupPartition	Partition the data by grouping together duplicated data

-- E --

em	EM algorithm starting with E-step for parameterized Gaussian mixture models
EMclust	BIC for Model-Based Clustering
emControl	Set control values for use with the EM algorithm
emE	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEEE	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEEI	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEEV	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEII	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEVE	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEVI	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emEVV	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emV	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVEE	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVEI	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVEV	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVII	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVVE	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVVI	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emVVV	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emX	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emXII	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emXXI	EM algorithm starting with E-step for a parameterized Gaussian mixture model
emXXX	EM algorithm starting with E-step for a parameterized Gaussian mixture model
entPlot	Plot Entropy Plots
errorBars	Draw error bars on a plot
estep	E-step for parameterized Gaussian mixture models.
estepE	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEEE	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEEI	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEEV	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEII	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEVE	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEVI	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepEVV	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepV	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVEE	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVEI	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVEV	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVII	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVVE	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVVI	E-step in the EM algorithm for a parameterized Gaussian mixture model.
estepVVV	E-step in the EM algorithm for a parameterized Gaussian mixture model.
EuroUnemployment	Unemployment data for European countries in 2014
ex4.1	Simulated Example Datasets From Baudry et al. (2010)
ex4.2	Simulated Example Datasets From Baudry et al. (2010)
ex4.3	Simulated Example Datasets From Baudry et al. (2010)
ex4.4.1	Simulated Example Datasets From Baudry et al. (2010)
ex4.4.2	Simulated Example Datasets From Baudry et al. (2010)

-- G --

gmmhd	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
gmmhdClassify	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
gmmhdClusterCores	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
GvHD	GvHD Dataset
GvHD.control	GvHD Dataset
GvHD.pos	GvHD Dataset

-- H --

hc	Model-based Agglomerative Hierarchical Clustering
hcE	Model-based Hierarchical Clustering
hcEEE	Model-based Hierarchical Clustering
hcEII	Model-based Hierarchical Clustering
hclass	Classifications from Hierarchical Agglomeration
hcRandomPairs	Random hierarchical structure
hcV	Model-based Hierarchical Clustering
hcVII	Model-based Hierarchical Clustering
hcVVV	Model-based Hierarchical Clustering
hdrlevels	Highest Density Region (HDR) Levels
hypvol	Aproximate Hypervolume for Multivariate Data

-- I --

icl	ICL for an estimated Gaussian Mixture Model
imputeData	Missing data imputation via the 'mix' package
imputePairs	Pairwise Scatter Plots showing Missing Data Imputations

-- L --

logLik.Mclust	Log-Likelihood of a 'Mclust' object
logLik.MclustDA	Log-Likelihood of a 'MclustDA' object
logsumexp	Log sum of exponentials

-- M --

majorityVote	Majority vote
map	Classification given Probabilities
mapClass	Correspondence between classifications
matchCluster	Missing data imputation via the 'mix' package
Mclust	Model-Based Clustering
mclust	Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
mclust.options	Default values for use with MCLUST package
mclust1Dplot	Plot one-dimensional data modeled by an MVN mixture.
mclust2Dplot	Plot two-dimensional data modelled by an MVN mixture
mclustBIC	BIC for Model-Based Clustering
mclustBICupdate	Update BIC values for parameterized Gaussian mixture models
MclustBootstrap	Resampling-based Inference for Gaussian finite mixture models
mclustBootstrapLRT	Bootstrap Likelihood Ratio Test for the Number of Mixture Components
MclustDA	MclustDA discriminant analysis
MclustDR	Dimension reduction for model-based clustering and classification
MclustDRrecoverdir	Subset selection for GMMDR directions based on BIC
MclustDRsubsel	Subset selection for GMMDR directions based on BIC
MclustDRsubsel1cycle	Subset selection for GMMDR directions based on BIC
MclustDRsubsel_classif	Subset selection for GMMDR directions based on BIC
MclustDRsubsel_cluster	Subset selection for GMMDR directions based on BIC
mclustICL	ICL Criterion for Model-Based Clustering
mclustLoglik	Log-likelihood from a table of BIC values for parameterized Gaussian mixture models
mclustModel	Best model based on BIC
mclustModelNames	MCLUST Model Names
MclustSSC	MclustSSC semi-supervised classification
mclustVariance	Template for variance specification for parameterized Gaussian mixture models
me	EM algorithm starting with M-step for parameterized MVN mixture models
me.weighted	EM algorithm with weights starting with M-step for parameterized Gaussian mixture models
meE	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEEE	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEEI	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEEV	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEII	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEVE	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEVI	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meEVV	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meV	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVEE	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVEI	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVEV	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVII	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVVE	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVVI	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meVVV	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meX	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meXII	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meXXI	EM algorithm starting with M-step for a parameterized Gaussian mixture model
meXXX	EM algorithm starting with M-step for a parameterized Gaussian mixture model
mstep	M-step for parameterized Gaussian mixture models
mstepE	M-step for a parameterized Gaussian mixture model
mstepEEE	M-step for a parameterized Gaussian mixture model
mstepEEI	M-step for a parameterized Gaussian mixture model
mstepEEV	M-step for a parameterized Gaussian mixture model
mstepEII	M-step for a parameterized Gaussian mixture model
mstepEVE	M-step for a parameterized Gaussian mixture model
mstepEVI	M-step for a parameterized Gaussian mixture model
mstepEVV	M-step for a parameterized Gaussian mixture model
mstepV	M-step for a parameterized Gaussian mixture model
mstepVEE	M-step for a parameterized Gaussian mixture model
mstepVEI	M-step for a parameterized Gaussian mixture model
mstepVEV	M-step for a parameterized Gaussian mixture model
mstepVII	M-step for a parameterized Gaussian mixture model
mstepVVE	M-step for a parameterized Gaussian mixture model
mstepVVI	M-step for a parameterized Gaussian mixture model
mstepVVV	M-step for a parameterized Gaussian mixture model
mvn	Univariate or Multivariate Normal Fit
mvnX	Univariate or Multivariate Normal Fit
mvnXII	Univariate or Multivariate Normal Fit
mvnXXI	Univariate or Multivariate Normal Fit
mvnXXX	Univariate or Multivariate Normal Fit

-- N --

nMclustParams	Number of Estimated Parameters in Gaussian Mixture Models
nVarParams	Number of Variance Parameters in Gaussian Mixture Models

-- P --

partconv	Numeric Encoding of a Partitioning
partuniq	Classifies Data According to Unique Observations
plot.clustCombi	Plot Combined Clusterings Results
plot.crimcoords	Discriminant coordinates data projection
plot.densityMclust	Plots for Mixture-Based Density Estimate
plot.gmmhd	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
plot.hc	Dendrograms for Model-based Agglomerative Hierarchical Clustering
plot.Mclust	Plotting method for Mclust model-based clustering
plot.mclustBIC	BIC Plot for Model-Based Clustering
plot.MclustBootstrap	Plot of bootstrap distributions for mixture model parameters
plot.mclustBootstrapLRT	Bootstrap Likelihood Ratio Test for the Number of Mixture Components
plot.MclustDA	Plotting method for MclustDA discriminant analysis
plot.MclustDR	Plotting method for dimension reduction for model-based clustering and classification
plot.mclustICL	ICL Plot for Model-Based Clustering
plot.MclustSSC	Plotting method for MclustSSC semi-supervised classification
plotDensityMclust1	Plots for Mixture-Based Density Estimate
plotDensityMclust2	Plots for Mixture-Based Density Estimate
plotDensityMclustd	Plots for Mixture-Based Density Estimate
plotEvalues.MclustDR	Plotting method for dimension reduction for model-based clustering and classification
predict.densityMclust	Density estimate of multivariate observations by Gaussian finite mixture modeling
predict.Mclust	Cluster multivariate observations by Gaussian finite mixture modeling
predict.MclustDA	Classify multivariate observations by Gaussian finite mixture modeling
predict.MclustDR	Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
predict.MclustSSC	Classification of multivariate observations by semi-supervised Gaussian finite mixtures
predict2D.MclustDR	Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
print.clustCombi	Combining Gaussian Mixture Components for Clustering
print.crimcoords	Discriminant coordinates data projection
print.gmmhd	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
print.hc	Model-based Agglomerative Hierarchical Clustering
print.Mclust	Model-Based Clustering
print.mclustBIC	BIC for Model-Based Clustering
print.MclustBootstrap	Resampling-based Inference for Gaussian finite mixture models
print.mclustBootstrapLRT	Bootstrap Likelihood Ratio Test for the Number of Mixture Components
print.MclustDA	MclustDA discriminant analysis
print.MclustDR	Dimension reduction for model-based clustering and classification
print.MclustDRsubsel	Subset selection for GMMDR directions based on BIC
print.mclustICL	ICL Criterion for Model-Based Clustering
print.mclustLoglik	Log-likelihood from a table of BIC values for parameterized Gaussian mixture models
print.MclustSSC	MclustSSC semi-supervised classification
print.summary.clustCombi	Combining Gaussian Mixture Components for Clustering
print.summary.crimcoords	Discriminant coordinates data projection
print.summary.gmmhd	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
print.summary.Mclust	Summarizing Gaussian Finite Mixture Model Fits
print.summary.mclustBIC	Summary function for model-based clustering via BIC
print.summary.MclustBootstrap	Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
print.summary.MclustDA	Summarizing discriminant analysis based on Gaussian finite mixture modeling
print.summary.MclustDR	Summarizing dimension reduction method for model-based clustering and classification
print.summary.mclustICL	ICL Criterion for Model-Based Clustering
print.summary.MclustSSC	Summarizing semi-supervised classification model based on Gaussian finite mixtures
printSummaryMclustBIC	Summary function for model-based clustering via BIC
printSummaryMclustBICn	Summary function for model-based clustering via BIC
priorControl	Conjugate Prior for Gaussian Mixtures.

-- Q --

quantileMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution

-- R --

randomOrthogonalMatrix	Random orthogonal matrix
randomPairs	Random hierarchical structure
randProj	Random projections of multidimensional data modeled by an MVN mixture

-- S --

sigma2decomp	Convert mixture component covariances to decomposition form.
sim	Simulate from Parameterized MVN Mixture Models
simE	Simulate from a Parameterized MVN Mixture Model
simEEE	Simulate from a Parameterized MVN Mixture Model
simEEI	Simulate from a Parameterized MVN Mixture Model
simEEV	Simulate from a Parameterized MVN Mixture Model
simEII	Simulate from a Parameterized MVN Mixture Model
simEVE	Simulate from a Parameterized MVN Mixture Model
simEVI	Simulate from a Parameterized MVN Mixture Model
simEVV	Simulate from a Parameterized MVN Mixture Model
simV	Simulate from a Parameterized MVN Mixture Model
simVEE	Simulate from a Parameterized MVN Mixture Model
simVEI	Simulate from a Parameterized MVN Mixture Model
simVEV	Simulate from a Parameterized MVN Mixture Model
simVII	Simulate from a Parameterized MVN Mixture Model
simVVE	Simulate from a Parameterized MVN Mixture Model
simVVI	Simulate from a Parameterized MVN Mixture Model
simVVV	Simulate from a Parameterized MVN Mixture Model
softmax	Softmax function
summary.clustCombi	Combining Gaussian Mixture Components for Clustering
summary.crimcoords	Discriminant coordinates data projection
summary.gmmhd	Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
summary.Mclust	Summarizing Gaussian Finite Mixture Model Fits
summary.mclustBIC	Summary function for model-based clustering via BIC
summary.MclustBootstrap	Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
summary.MclustDA	Summarizing discriminant analysis based on Gaussian finite mixture modeling
summary.MclustDR	Summarizing dimension reduction method for model-based clustering and classification
summary.MclustDRsubsel	Subset selection for GMMDR directions based on BIC
summary.mclustICL	ICL Criterion for Model-Based Clustering
summary.MclustSSC	Summarizing semi-supervised classification model based on Gaussian finite mixtures
summaryMclustBIC	Summary function for model-based clustering via BIC
summaryMclustBICn	Summary function for model-based clustering via BIC
surfacePlot	Density or uncertainty surface for bivariate mixtures

-- T --

Test1D	Simulated Example Datasets From Baudry et al. (2010)
thyroid	UCI Thyroid Gland Data

-- U --

uncerPlot	Uncertainty Plot for Model-Based Clustering
unmap	Indicator Variables given Classification

-- W --

wdbc	UCI Wisconsin Diagnostic Breast Cancer Data
wreath	Data Simulated from a 14-Component Mixture