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HPFMM Procedure


The HPFMM procedure is a high-performance counterpart of the FMM procedure that fits statistical models to data for which the distribution of the response is a finite mixture of univariate distributions-that is, each response comes from one of several random univariate distributions that have unknown probabilities. It is a high-performance version of the FMM procedure in SAS/STAT software. PROC HPFMM runs in either single-machine mode or distributed mode. The procedure enables you to do the following:

  • model the component distributions in addition to the mixing probabilities
  • fit finite mixture models by maximum likelihood or Bayesian methods
  • fit finite mixtures of regression and generalized linear models
  • model overdispersed data
  • perform Bayesian analysis
  • estimate multimodal or heavy-tailed densities
  • fit zero-inflated or hurdle models to count data with excess zeros
  • specify the response variable by using either the response syntax or the events/trials syntax
  • specify constraints among the parameters of the mixture model for multithreaded and distributed computing
  • performs weighted estimation
  • specify performance options for multithreaded and distributed computing

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

Examples