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HPCANDISC Procedure


The HPCANDISC procedure performs canonical discriminant analysis and is a high-performance version of the CANDISC procedure in SAS/STAT software. Canonical discriminant analysis is a dimension-reduction technique related to principal component analysis and canonical correlation. PROC HPCANDISC runs in either single-machine mode or distributed mode. The procedure enables you to do the following:

  • performs a canonical discriminant analysis
  • computes squared Mahalanobis distances between class means
  • performs both univariate and one-way multivariate analyses of variance
  • perform weighted analysis
  • display both standardized and unstandardized canonical coefficients
  • display correlations between the canonical variables and the original variables as well as the class means for the canonical variables
  • test the hypothesis that each canonical correlation and all smaller canonical correlations are zero in the population
  • create a data set that contains the canonical coefficients
  • create a data set that contains scored canonical variables
  • specify performance options for multithreaded and distributed computing

For further details see the SAS/STAT User's Guide: The HPCANDISC Procedure
( PDF | HTML )

Examples