Step-Wise Clustering Procedures

Abstract A simple step-wise procedure for the clustering of variables is described. Two alternative criteria for the merger of groups at each pass are discussed: (1) maximization of the pairwise correlation between the centroids of two groups, and (2) minimization of Wilks' statistic to test the hypothesis of independence between two groups. For a set of sample covariance matrices the step-wise solution for each criterion is compared with the optimal two-group separation of variables found by total enumeration of the possible groupings.