ACECLUS Procedure
The ACECLUS procedure obtains approximate estimates of the pooled withincluster covariance matrix when the clusters are assumed to
be multivariate normal with equal covariance matrices. Neither cluster membership nor the number of clusters needs to be known.
PROC ACECLUS is useful for preprocessing data to be subsequently clustered by the CLUSTER or FASTCLUS procedure.
The procedure enables you to do the following:
 choose between the following clustering methods:
 use a number of pairs, m, with the smallest distances to form the estimate at each iteration
 use all pairs closer than a given cutoff value to form the estimate at each iteration
 specify the metric in which computations are performed
 specify the number or proportion of pairs for estimating withincluster covariance
 specify the threshold for including pairs in the estimation of the withincluster covariance

 perform BY group processing, which enables you to obtain separate analyses on grouped observations
 perform weighted analysis
 create a data set that corresponds to any output table
 create a data set that contains means, standard deviations, number of observations, covariances,
estimated withincluster covariances, eigenvalues, and canonical coefficients
 produce a PPplot of distances between pairs from last iteration
 produce a QQplot of power transformation of distances between pairs from last iteration

For further details see the ACECLUS Procedure
Examples