# The HPCOUNTREG Procedure

The HPCOUNTREG procedure is a high-performance version of the COUNTREG procedure in SAS/ETS^{®} software. Like the COUNTREG procedure, the HPCOUNTREG procedure fits regression models in which
the dependent variable takes on nonnegative integer or count values.

Unlike the COUNTREG procedure, which can be run only on an individual workstation, the HPCOUNTREG procedure takes advantage of a computing environment that enables it to distribute the optimization task
among one or more nodes. In addition, each node can use one or more threads to carry out the optimization on its subset of the data. When several nodes are used, with each node using several threads to
carry out its part of the work, the result is a highly parallel computation that provides a dramatic gain in performance.

The HPCOUNTREG procedure estimates the parameters of a count regression model by maximum likelihood techniques and supports the following models for count data:

- Poisson regression
- Conway-Maxwell-Poisson regression
- negative binomial regression with quadratic and linear variance functions
- zero-inflated Poisson (ZIP) model
- zero-inflated Conway-Maxwell-Poisson (ZICMP) model
- zero-inflated negative binomial (ZINB) model
- fixed-effects and random-effects Poisson models for panel data
- fixed-effects and random-effects negative binomial models for panel data

## Documentation

For further details, see the *SAS/ETS*^{®} User's Guide: High Performance Procedures

## Examples