SAS/STAT Software


The HPGENSELECT procedure is a high-performance procedure that provides model fitting and model building for generalized linear models. The following are highlights of the HPGENSELECT procedure's features:

  • fits models for standard distributions in the exponential family
  • fits multinomial models for ordinal and nominal responses
  • fits zero-inflated Poisson and negative binomial models for count data
  • supports the following link functions:
    • complementary log-log
    • generalized logit
    • identity
    • reciprocal
    • reciprocal squared
    • logarithm
    • logit
    • log-log
    • probit
  • provides forward, backward, and stepwise variable selection
  • supports the following selection criteria:
    • AIC (Akaike's information criterion)
    • AICC (small-sample bias corrected version of Akaike's information criterion)
    • BIC (Schwarz Bayesian criterion)
  • writes SAS DATA step code for computing predicted values of the fitted model either to a file or to a catalog entry
  • creates a data set that contains observationwise statistics that are computed after the model is fitted
  • enables you to specify how observations in the input data set are to be logically partitioned into disjoint subsets for model training, validation, and testing
  • performs weighted estimation
  • runs in either single-machine mode or distributed mode

For further details see the HPGENSELECT Procedure