SAS/STAT Software

ACECLUS Procedure

The ACECLUS procedure obtains approximate estimates of the pooled within-cluster 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 within-cluster covariance
  • specify the threshold for including pairs in the estimation of the within-cluster 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 within-cluster covariances, eigenvalues, and canonical coefficients
  • produce a PP-plot of distances between pairs from last iteration
  • produce a QQ-plot of power transformation of distances between pairs from last iteration

For further details see the ACECLUS Procedure