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


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Documentation for package ‘mclust’ version 6.1.1

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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