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.