The CNTSELECT Procedure
Functional Summary
Table 1 summarizes the statements and options used with the CNTSELECT procedure.
Table 1: Functional Summary
| Description | Statement | Option |
|---|---|---|
| Data Table Options | ||
| Specifies the input data table | PROC CNTSELECT | DATA= |
| Specifies the identification variable for panel data analysis | PROC CNTSELECT | GROUPID= |
| Writes estimates to an output data table | OUTPUT | OUT= |
| Specifies BY-group processing | BY | |
| Specifies the classification variables | CLASS | |
| Specifies an optional frequency variable | FREQ | |
| Specifies an optional weight variable | WEIGHT | |
| Printing Control Options | ||
| Prints the correlation matrix of the estimates | PROC CNTSELECT | CORRB |
| Prints the covariance matrix of the estimates | PROC CNTSELECT | COVB |
| Suppresses the normal printed output | PROC CNTSELECT | NOPRINT |
| Requests all printing options | PROC CNTSELECT | PRINTALL |
| Prints timing information | PROC CNTSELECT | PRINTTIMING |
| Prints the names used internally for the parameters | PROC CNTSELECT | PRINTINTERNALNAMES |
| Options to Control the Optimization Process | ||
| Selects the iterative minimization method to use | PROC CNTSELECT | METHOD= |
| Specifies maximum number of iterations allowed | PROC CNTSELECT | MAXITER= |
| Specifies maximum number of function calls | PROC CNTSELECT | MAXFUNC= |
| Specifies the upper limit of CPU time in seconds | PROC CNTSELECT | MAXTIME= |
| Sets boundary restrictions on parameters | BOUNDS | |
| Sets initial values for parameters | INIT | |
| Sets linear restrictions on parameters | RESTRICT | |
| Model Estimation Options | ||
| Specifies the dispersion variables | DISPMODEL | |
| Specifies the type of model | PROC CNTSELECT | DIST= |
| Specifies the type of covariance matrix | PROC CNTSELECT | 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 the Conway-Maxwell-Poisson (CMP) model | MODEL | PARAMETER= |
| Specifies the zero-inflated offset variable | ZEROMODEL | OFFSET= |
| Specifies the zero-inflated link function | ZEROMODEL | LINK= |
| Specifies the constructed regression effects | EFFECT | |
| Regression Effect-Selection Options | ||
| Specifies the selection method | SELECTION | METHOD= |
| Specifies how to apply the STOP= criterion | SELECTION | STOPHORIZON= |
| Regression Effect-Selection Method Options | ||
| Specifies a criterion for choosing the best model at each step | SELECTION | CHOOSE= |
| Specifies that the competitive form of the stepwise selection method be used | SELECTION | COMPETITIVE |
| Specifies the maximum number of effects in the model | SELECTION | MAXEFFECTS= |
| Specifies the maximum number of selection steps | SELECTION | MAXSTEPS= |
| Specifies the minimum number of effects in the model | SELECTION | MINEFFECTS= |
| Specifies a criterion to decide which effects enter or leave the model at each step | SELECTION | SELECT= |
| Specifies a criterion for stopping the selection process | SELECTION | STOP= |
| Bayesian Markov Chain Monte Carlo (MCMC) Options | ||
| Specifies the number of burn-in iterations | BAYES | NBURNIN= |
| Specifies the number of iterations to run during the sampling phase | BAYES | NSAMPLE= |
| Specifies the MCMC sampler and its options | BAYES | SAMPLER= |
| Specifies the random number generator seed | BAYES | SEED= |
| Controls the thinning of the Markov chain | BAYES | THIN= |
| Bayesian Output Tables | ||
| Displays MCMC diagnostics | BAYES | DIAGNOSTICS= |
| Displays the settings used for all MCMC diagnostics | BAYES | DIAGNOSTICS(SETTINGS)= |
| Displays a summary of all parameters and their priors | BAYES | PRIORSUMMARY |
| Displays the settings used for the MCMC sampler | BAYES | SAMPLERSETTINGS |
| Displays a summary of the MCMC sampler used | BAYES | SAMPLERSUMMARY |
| Displays posterior summary statistics | BAYES | STATISTICS= |
| Bayesian Posterior Sample | ||
| Specifies options for saving a SAS data table for the posterior sample | BAYES | OUTPOST= |
| Bayesian Prior Options | ||
| Specifies the Cauchy prior distribution | PRIOR | CAUCHY() |
| Specifies the gamma prior distribution | PRIOR | GAMMA() |
| Specifies the inverse gamma prior distribution | PRIOR | IGAMMA() |
| Specifies the normal prior distribution | PRIOR | NORMAL() |
| Specifies the square root gamma prior distribution | PRIOR | SQRTGAMMA() |
| Specifies the square root inverse gamma prior distribution | PRIOR | SQRTIGAMMA() |
| Specifies the t prior distribution | PRIOR | T() |
| Specifies the uniform prior distribution | PRIOR | UNIFORM() |
| Output Control Options | ||
| Specifies the ODS tables to display | DISPLAY | |
| Specifies the ODS tables to save as CAS output tables | DISPLAYOUT | |
| Specifies the output item store to preserve the properties of the model and the results of fitting the model | PROC CNTSELECT | STORE= |
| Outputs SAS variables to the output data table | OUTPUT | COPYVAR= |
| Outputs the estimates of dispersion for the CMP model | OUTPUT | DISPERSION |
| Outputs the estimates of GDelta for the CMP model | OUTPUT | GDELTA= |
| Outputs the estimates of for the CMP model | OUTPUT | LAMBDA= |
| Outputs the estimates of for the CMP model | OUTPUT | NU= |
| Outputs the estimates of 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 | OUTPUT | XBETA= |
| Outputs estimates of ZGamma | OUTPUT | ZGAMMA= |
| Outputs probability of a zero value as a result of the zero-generating process | OUTPUT | PROBZERO= |
Last updated: April 15, 2021