The HPCOUNTREG Procedure
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Overview
- Getting Started
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Syntax
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DetailsMissing ValuesPoisson RegressionConway-Maxwell-Poisson RegressionNegative Binomial RegressionZero-Inflated Count Regression OverviewZero-Inflated Poisson RegressionZero-Inflated Conway-Maxwell-Poisson RegressionZero-Inflated Negative Binomial RegressionParameter Naming Conventions for the RESTRICT, TEST, BOUNDS, and INIT StatementsComputational ResourcesCovariance Matrix TypesDisplayed OutputOUTPUT OUT= Data SetOUTEST= Data SetODS Table Names
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Examples
- References
OUTPUT OUT= Data Set
The OUTPUT statement creates a new SAS data set that contains various estimates that you specify. You can request that the
output data set contain the estimates of 
, the expected value of the response variable, and the probability that the response variable will take the current value.
In a zero-inflated model, you can also request that the output data set contain the estimates of 
, and the probability that the response is zero as a result of the zero-generating process. In a Conway-Maxwell-Poisson model,
you can also request that the output data set contains estimates of 
, 
, 
, 
, mode, variance and dispersion.
Except for the probability of the current value, these statistics can be computed for all observations in which the regressors are not missing, even if the response is missing. By adding observations with missing response values to the input data set, you can compute these statistics for new observations or for settings of the regressors that are not present in the data without affecting the model fit. Because of potential space limitations on the client workstation, the data set that is created by the OUTPUT statement does not contain the variables in the input data set.