awe | Approximate weight of evidence for model-based hierarchical clustering. |
bic | BIC for parameterized MVN mixture models |
censcale | Centering and Scaling of Data |
clpairs | Classifications for hierarchical clustering. |
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 | E-step for parameterized MVN mixture models |
estep.EEE | E-step for constant-variance MVN mixture models |
estep.EI | E-step for spherical, constant-volume 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 |
loglik | Loglikelihood for model-based hierarchical clustering. |
me | EM for parameterized MVN mixture models |
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.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 | Classification Tree for Model-based Gaussian 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.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 | M-step for parameterized MVN mixture models |
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.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 |
partuniq | Classifies Data According to Unique Observations |
summary.emclust | Summary method for `emclust' objects. |
summary.emclust1 | Summary method for `emclust1' objects. |