The HPGENSELECT procedure does the following:

  • estimates the parameters of a generalized linear regression model by using maximum likelihood techniques

  • provides model-building syntax in the CLASS statement and the effect-based MODEL statement, which are familiar from SAS/STAT procedures (in particular, the GLM, GENMOD, LOGISTIC, GLIMMIX, and MIXED procedures)

  • enables you to split classification effects into individual components by using the SPLIT option in the CLASS statement

  • permits any degree of interaction effects that involve classification and continuous variables

  • provides multiple link functions

  • provides models for zero-inflated count data

  • provides cumulative link modeling for ordinal data and generalized logit modeling for unordered multinomial data

  • enables model building (variable selection) through the SELECTION statement

  • provides a WEIGHT statement for weighted analysis

  • provides a FREQ statement for grouped analysis

  • provides an OUTPUT statement to produce a data set that has predicted values and other observationwise statistics

Because the HPGENSELECT procedure is a high-performance analytical procedure, it also does the following:

  • enables you to run in distributed mode on a cluster of machines that distribute the data and the computations

  • enables you to run in single-machine mode on the server where SAS is installed

  • exploits all the available cores and concurrent threads, regardless of execution mode

For more information, see the section Processing Modes in Chapter 3: Shared Concepts and Topics.