A Two-Stage Clustering Algorithm with Robust Recovery Characteristics

Two FORTRAN IV computer programs for a two-stage clustering algorithm with robust recovery characteristics are described. In Stage 1, a group average hierarchical algorithm generates cluster centroids which are used as starting seed points for Stage 2, Jancey's k-means nonhierarchical algorithm. Also available with the hierarchical algorithm is a hypothesis test procedure which can be used to determine whether significant cluster structure exists in the data.