Baudry_etal_2010_JCGS_examples
                        Simulated Example Datasets From Baudry et al.
                        (2010)
BrierScore              Brier score to assess the accuracy of
                        probabilistic predictions
EuroUnemployment        Unemployment data for European countries in
                        2014
GvHD                    GvHD Dataset
Mclust                  Model-Based Clustering
MclustBootstrap         Resampling-based Inference for Gaussian finite
                        mixture models
MclustDA                MclustDA discriminant analysis
MclustDR                Dimension reduction for model-based clustering
                        and classification
MclustDRsubsel          Subset selection for GMMDR directions based on
                        BIC
MclustSSC               MclustSSC semi-supervised classification
acidity                 Acidity data
adjustedRandIndex       Adjusted Rand Index
banknote                Swiss banknotes data
bic                     BIC for Parameterized Gaussian Mixture Models
cdens                   Component Density for Parameterized MVN Mixture
                        Models
cdensE                  Component Density for a Parameterized MVN
                        Mixture Model
cdfMclust               Cumulative Distribution and Quantiles for a
                        univariate Gaussian mixture distribution
chevron                 Simulated minefield data
clPairs                 Pairwise Scatter Plots showing Classification
classError              Classification error
classPriorProbs         Estimation of class prior probabilities by EM
                        algorithm
clustCombi              Combining Gaussian Mixture Components for
                        Clustering
clustCombiOptim         Optimal number of clusters obtained by
                        combining mixture components
combMat                 Combining Matrix
combiPlot               Plot Classifications Corresponding to
                        Successive Combined Solutions
combiTree               Tree structure obtained from combining mixture
                        components
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
cvMclustDA              MclustDA cross-validation
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
em                      EM algorithm starting with E-step for
                        parameterized Gaussian mixture models
emControl               Set control values for use with the EM
                        algorithm
emE                     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.
gmmhd                   Identifying Connected Components in Gaussian
                        Finite Mixture Models for Clustering
hc                      Model-based Agglomerative Hierarchical
                        Clustering
hcE                     Model-based Hierarchical Clustering
hcRandomPairs           Random hierarchical structure
hclass                  Classifications from Hierarchical Agglomeration
hdrlevels               Highest Density Region (HDR) Levels
hypvol                  Aproximate Hypervolume for Multivariate Data
icl                     ICL for an estimated Gaussian Mixture Model
imputeData              Missing data imputation via the 'mix' package
imputePairs             Pairwise Scatter Plots showing Missing Data
                        Imputations
logLik.Mclust           Log-Likelihood of a 'Mclust' object
logLik.MclustDA         Log-Likelihood of a 'MclustDA' object
logsumexp               Log sum of exponentials
majorityVote            Majority vote
map                     Classification given Probabilities
mapClass                Correspondence between classifications
mclust-package          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
mclustBootstrapLRT      Bootstrap Likelihood Ratio Test for the Number
                        of Mixture Components
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
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
mstep                   M-step for parameterized Gaussian mixture
                        models
mstepE                  M-step for a parameterized Gaussian mixture
                        model
mvn                     Univariate or Multivariate Normal Fit
mvnX                    Univariate or Multivariate Normal Fit
nMclustParams           Number of Estimated Parameters in Gaussian
                        Mixture Models
nVarParams              Number of Variance Parameters in Gaussian
                        Mixture Models
partconv                Numeric Encoding of a Partitioning
partuniq                Classifies Data According to Unique
                        Observations
plot.Mclust             Plotting method for Mclust model-based
                        clustering
plot.MclustBootstrap    Plot of bootstrap distributions for mixture
                        model parameters
plot.MclustDA           Plotting method for MclustDA discriminant
                        analysis
plot.MclustDR           Plotting method for dimension reduction for
                        model-based clustering and classification
plot.MclustSSC          Plotting method for MclustSSC semi-supervised
                        classification
plot.clustCombi         Plot Combined Clusterings Results
plot.densityMclust      Plots for Mixture-Based Density Estimate
plot.hc                 Dendrograms for Model-based Agglomerative
                        Hierarchical Clustering
plot.mclustBIC          BIC Plot for Model-Based Clustering
plot.mclustICL          ICL Plot for Model-Based Clustering
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
predict.densityMclust   Density estimate of multivariate observations
                        by Gaussian finite mixture modeling
priorControl            Conjugate Prior for Gaussian Mixtures.
randProj                Random projections of multidimensional data
                        modeled by an MVN mixture
randomOrthogonalMatrix
                        Random orthogonal matrix
sigma2decomp            Convert mixture component covariances to
                        decomposition form.
sim                     Simulate from Parameterized MVN Mixture Models
simE                    Simulate from a Parameterized MVN Mixture Model
softmax                 Softmax function
summary.Mclust          Summarizing Gaussian Finite Mixture Model Fits
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.MclustSSC       Summarizing semi-supervised classification
                        model based on Gaussian finite mixtures
summary.mclustBIC       Summary function for model-based clustering via
                        BIC
surfacePlot             Density or uncertainty surface for bivariate
                        mixtures
thyroid                 UCI Thyroid Gland Data
uncerPlot               Uncertainty Plot for Model-Based Clustering
unmap                   Indicator Variables given Classification
wdbc                    UCI Wisconsin Diagnostic Breast Cancer Data
wreath                  Data Simulated from a 14-Component Mixture
