PROC HPCOUNTREG produces the following displayed output.
The "Model Fit Summary" table contains the following information:
dependent (count) variable name
number of observations used
number of missing values in data set, if any
data set name
type of model that was fit
offset variable name, if any
zero-inflated link function, if any
zero-inflated offset variable name, if any
log-likelihood value at solution
maximum absolute gradient at solution
number of iterations
AIC value at solution (smaller value indicates better fit)
SBC value at solution (smaller value indicates better fit)
A line in the "Model Fit Summary" table indicates whether the algorithm successfully converged.
The "Parameter Estimates" table in the displayed output gives the estimates for the ZI intercept and ZI explanatory variables; they are labeled with the prefix "Inf_". For example, the ZI intercept is labeled "Inf_intercept". If you specify "Age" (a variable in your data set) as a ZI explanatory variable, then the "Parameter Estimates" table labels the corresponding parameter estimate "Inf_Age". If you do not list any ZI explanatory variables (for the ZI option VAR=), then only the intercept term is estimated.
"_Alpha" is the negative binomial dispersion parameter. The t statistic that is given for "_Alpha" is a test of overdispersion.
If you specify the COVB option in the PROC HPCOUNTREG or MODEL statement, the HPCOUNTREG procedure displays the estimated covariance matrix, which is defined as the inverse of the information matrix at the final iteration.