fpc: Flexible procedures for clustering
Various methods for clustering and cluster validation.
Fixed point clustering. Linear regression clustering.
Clustering by merging Gaussian mixture components. Symmetric
and asymmetric discriminant projections for visualisation of
the separation of groupings. Cluster validation statistics for
distance based clustering including corrected Rand index.
Clusterwise cluster stability assessment. Methods for
estimation of the number of clusters: Calinski-Harabasz,
Tibshirani and Walther's prediction strength.
Gaussian/multinomial mixture fitting for mixed
continuous/categorical variables. Veriablewise statistics for
cluster interpretation. DBSCAN clustering. Interface functions
for many clustering methods implemented in R, including
estimating the number of clusters with kmeans, pam and clara.
Modality diagnosis for Gaussian mixtures. Note that the use of
the package mclust (called by function prabclust) is protected
by a special license, see
http://www.stat.washington.edu/mclust/license.txt. For an
overview see package?fpc.