The HPCOUNTREG procedure estimates the parameters of a count regression model by maximum likelihood techniques. The following list summarizes some basic features of the HPCOUNTREG procedure:
can perform analysis on a massively parallel high-performance appliance
reads input data in parallel and writes output data in parallel when the data source is the appliance database
is highly multithreaded during all phases of analytic execution
performs maximum likelihood estimation
supports multiple link functions
uses the WEIGHT statement for weighted analysis
uses the FREQ statement for grouped analysis
uses the OUTPUT statement to produce a data set that contains predicted probabilities and other observationwise statistics