Model-based cluster analysis


[Package List] [Top]
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