awe                     Approximate weight of evidence for model-based
                        hierarchical clustering.
bic                     BIC for parameterized MVN mixture models
censcale                Centering and Scaling of Data
chevron                 Simulated minefield data
clpairs                 Classifications for hierarchical clustering.
diabetes                Diabetes data
emclust                 BIC from hierarchical clustering followed by
                        EM for several parameterized Gaussian mixture
                        models.
emclust1                BIC from hierarchical clustering followed by
                        EM for a parameterized Gaussian mixture model.
estep.EEE               E-step for constant-variance MVN mixture
                        models
estep.EI                E-step for spherical, constant-volume MVN
                        mixture models
estep                   E-step for parameterized MVN mixture models
estep.VI                E-step for spherical, varying volume MVN
                        mixture models
estep.VVV               E-step for constant-variance MVN mixture
                        models
estep.XEV               E-step for constant shape MVN mixture models
hypvol                  Estimation of hypervolume
loglik                  Loglikelihood for model-based hierarchical
                        clustering.
me.EEE                  EM for constant-variance MVN mixture models
me.EEV                  EM for constant shape, constant volume MVN
                        mixture models
me.EI                   EM for spherical, constant-volume MVN mixture
                        models
me                      EM for parameterized MVN mixture models
me.VEV                  EM for constant shape, varying volume MVN
                        mixture models
me.VI                   EM for spherical, varying volume MVN mixture
                        models
me.VVV                  EM for unconstrained MVN mixture models
mhclass                 Classifications for hierarchical clustering.
mhtree.EEE              Classification tree for hierarchical
                        clustering for Gaussian models with constant
                        variance.
mhtree.EFV              Classification tree for hierarchical
                        clustering for Gaussian models with equal
                        volume and fixed shape.
mhtree.EI               Classification tree for hierarchical
                        clustering for Gaussian models with uniform
                        diagonal variance.
mhtree                  Classification Tree for Model-based Gaussian
                        hierarchical clustering.
mhtree.VFV              Classification tree for hierarchical
                        clustering for Gaussian models with equal
                        volume and constant shape.
mhtree.VI               Classification tree for hierarchical
                        clustering for Gaussian models with diagonal
                        variance.
mhtree.VVV              Classification tree for hierarchical
                        clustering for Gaussian models with
                        unconstrained variance.
mixproj                 Displays one standard deviation of an MVN
                        mixture classification.
mstep.EEE               M-step for constant-variance MVN mixture
                        models
mstep.EEV               M-step for constant shape, constant volume MVN
                        mixture models
mstep.EI                M-step for spherical, constant-volume MVN
                        mixture models
mstep                   M-step for parameterized MVN mixture models
mstep.VEV               M-step for constant shape, constant volume MVN
                        mixture models
mstep.VI                M-step for spherical, varying volume MVN
                        mixture models
mstep.VVV               M-step for unconstrained MVN mixture models
one.XXX                 Log-likelihood for a single cluster
partconv                Convert partitioning into numerical vector.
partuniq                Classifies Data According to Unique
                        Observations
plot.emclust            Plot BIC values
print.emclust           Print methods for BIC values
summary.emclust         Summary method for 'emclust' objects.
summary.emclust1        Summary method for 'emclust1' objects.
traceW                  Compute traceW
ztoc                    Conversion between conditional probabilities
                        and a classification
