The HPCOUNTREG Procedure
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 
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.