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

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Documentation for package ‘mclust’ version 5.3

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

mclust-package Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation

-- A --

acidity Acidity data
adjustedRandIndex Adjusted Rand Index

-- 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

-- 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
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.
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

-- 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.
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 Hierarchical Clustering
hcE Model-based Hierarchical Clustering
hcEEE Model-based Hierarchical Clustering
hcEII Model-based Hierarchical Clustering
hclass Classifications from Hierarchical Agglomeration
hcV Model-based Hierarchical Clustering
hcVII Model-based Hierarchical Clustering
hcVVV Model-based Hierarchical Clustering
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

-- 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 Normal Mixture Modeling 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
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
mclustModel Best model based on BIC
mclustModelNames MCLUST Model Names
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 MVN 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.densityMclust Plots for Mixture-Based Density Estimate
plot.gmmhd Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
plot.Mclust Plot Model-Based Clustering Results
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
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
predict2D.MclustDR Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
print.clustCombi Combining Gaussian Mixture Components for Clustering
print.gmmhd Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
print.hc Model-based 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.summary.clustCombi Combining Gaussian Mixture Components for Clustering
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
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 --

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
summary.clustCombi Combining Gaussian Mixture Components for Clustering
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
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 Thyroid gland data

-- U --

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

-- W --

wreath Data Simulated from a 14-Component Mixture