The COUNTREG Procedure

Functional Summary

Table 11.1 summarizes statements and that you can use in the COUNTREG procedure.

Table 11.1: PROC COUNTREG Functional Summary

Description

Statement

Option

Data Set Options

   

Specifies the input data set

COUNTREG

DATA=

Specifies the ID variable for panel data analysis

COUNTREG

GROUPID=

Writes parameter estimates to an output data set

COUNTREG

OUTEST=

Requests that the procedure produce graphics via the Output Delivery System

COUNTREG

PLOTS=

Writes estimates to an output data set

OUTPUT

OUT=

Declaring the Role of Variables

   

Specifies BY-group processing

BY

 

Specifies classification variables

CLASS

 

Specifies a frequency variable

FREQ

 

Specifies a weight variable

WEIGHT

 

Item Store Control Options

   

Displays the contents of the item store

SHOW

 

Stores the model in an item store

STORE

 

Restores the model from the item store

COUNTREG

RESTORE=

Printing Control Options

   

Prints the correlation matrix of the estimates

MODEL

CORRB

Prints the covariance matrix of the estimates

MODEL

COVB

Prints a summary iteration listing

MODEL

ITPRINT

Suppresses the normal printed output

COUNTREG

NOPRINT

Requests all printing options

MODEL

PRINTALL

Option Process Control Options

   

Specifies maximum number of iterations allowed

MODEL

MAXITER=

Selects the iterative minimization method to use

COUNTREG

METHOD=

Sets boundary restrictions on parameters

BOUNDS

 

Sets initial values for parameters

INIT

 

Sets linear restrictions on parameters

RESTRICT

 

Specifies the optimization options

NLOPTIONS

See Chapter 6: Nonlinear Optimization Methods

Model Estimation Options

   

Specifies the dispersion variables

DISPMODEL

 

Specifies the type of model

COUNTREG

DIST=

Specifies the type of covariance matrix

MODEL

COVEST=

Specifies the type of error components model for panel data

MODEL

ERRORCOMP=

Suppresses the intercept parameter

MODEL

NOINT

Specifies the offset variable

MODEL

OFFSET=

Specifies the parameterization for Conway-Maxwell-Poisson (CMP) model

MODEL

PARAMETER=

Specifies the zero-inflated offset variable

ZEROMODEL

OFFSET=

Specifies the zero-inflated link function

ZEROMODEL

LINK=

Specifies variable selection

MODEL

SELECT=( )

Output Control Options

   

Includes covariances in the OUTEST= data set

COUNTREG

COVOUT

Outputs the estimates of dispersion for the CMP model

OUTPUT

DISPERSION

Outputs the estimates of GDelta $=\mathbf{g}_{i}’\bdelta $ for CMP model

OUTPUT

GDELTA=

Outputs the estimates of $\lambda $ for the CMP model

OUTPUT

LAMBDA=

Outputs the estimates of $\nu $ for the CMP model

OUTPUT

NU=

Outputs the estimates of $\mu $ for the CMP model

OUTPUT

MU=

Outputs the estimates of mode for the CMP model

OUTPUT

MODE=

Outputs the probability that the response variable will take the current value

OUTPUT

PROB=

Outputs probabilities for particular response values

OUTPUT

PROBCOUNT( )

Outputs expected value of response variable

OUTPUT

PRED=

Outputs the estimates of variance for the CMP model

OUTPUT

VARIANCE=

Outputs estimates of XBeta $=\mathbf{x}_{i}’\bbeta $

OUTPUT

XBETA=

Outputs estimates of ZGamma $=\mathbf{z}_{i}’\bgamma $

OUTPUT

ZGAMMA=

Outputs the probability that the response variable will take a zero value as a result of the zero-generating process

OUTPUT

PROBZERO=

Specifies the input data set for scoring

SCORE

DATA=

Specifies the output data set for scoring

SCORE

OUT=

Outputs the estimates of dispersion for the CMP model

SCORE

DISPERSION

Outputs the estimates of GDelta $=\mathbf{g}_{i}’\bdelta $ for the CMP model

SCORE

GDELTA=

Outputs the estimates of $\lambda $ for the CMP model

SCORE

LAMBDA=

Outputs the estimates of $\nu $ for the CMP model

SCORE

NU=

Outputs the estimates of $\mu $ for the CMP model

SCORE

MU=

Outputs the estimates of mode for the CMP model

SCORE

MODE=

Outputs the probability that the response variable will take the current value

SCORE

PROB=

Outputs probabilities for particular response values

SCORE

PROBCOUNT( )

Outputs expected value of response variable

SCORE

PRED=

Outputs the estimates of variance for the CMP model

SCORE

VARIANCE=

Outputs estimates of XBeta $=\mathbf{x}_{i}’\bbeta $

SCORE

XBETA=

Outputs estimates of ZGamma $=\mathbf{z}_{i}’\bgamma $

SCORE

ZGAMMA=

Outputs the probability that the response variable will take a zero value as a result of the zero-generating process

SCORE

PROBZERO=