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. |
ctoz |
Conversion between conditional probabilities and a classification |
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 |
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 |
hypvol |
Estimation of hypervolume |
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.VEV |
Classification tree for hierarchical clustering for Gaussian models with equal volume and constant shape. |
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 |
mvn2plot |
Displays one standard deviation of an MVN mixture classification. |
one.XI |
Log-likelihood for a single cluster |
one.XXX |
Log-likelihood for a single cluster |
partconv |
Convert partitioning into numerical vector. |
partuniq |
Classifies Data According to Unique Observations |
pcvol |
Estimation of hypervolume |
plot.emclust |
Plot BIC values |
plot.emclust1 |
Plot BIC values |
print.bic |
Print methods for BIC values |
print.emclust |
Print methods for BIC values |
print.emclust1 |
Print methods for BIC values |
print.mhtree |
Classification Tree for Model-based Gaussian hierarchical clustering. |
print.summary.emclust |
Summary method for `emclust' objects. |
print.summary.emclust1 |
Summary method for `emclust1' objects. |
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 |