CQLIM Procedure
Functional Summary
Table 1 summarizes the statements and options available in the CQLIM procedure.
Table 1: Functional Summary
| Description | Statement | Option |
|---|---|---|
| Data Table Options | ||
| Specifies the input data table | PROC CQLIM | DATA= |
| Writes predictions to an output data table | 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 | NONORMALIZE |
| Printing Control Options | ||
| Prints the correlation matrix of the estimates | PROC CQLIM | CORRB |
| Prints the covariance matrix of the estimates | PROC CQLIM | COVB |
| Prints a summary iteration listing | PROC CQLIM | ITPRINT |
| Optimization Process Control Options | ||
| Specifies the maximum number of iterations | PROC CQLIM | MAXITER= |
| Selects the iterative minimization method to use | PROC CQLIM | METHOD= |
| Sets boundary restrictions on parameters | BOUNDS | |
| Sets initial values for parameters | INIT | |
| Sets linear restrictions on parameters | RESTRICT | |
| Model Estimation Options | ||
| Specifies the method to calculate parameter covariance | PROC CQLIM | COVEST= |
| Specifies the number of draws for Monte Carlo integration | PROC CQLIM | NDRAW= |
| Suppresses the intercept parameter | MODEL | NOINT |
| Specifies a seed for pseudorandom number generation | PROC CQLIM | SEED= |
| Bayesian Markov Chain Monte Carlo (MCMC) Options | ||
| Specifies the number of burn-in iterations | BAYES | NBURNIN= |
| Specifies the number of Markov chains to run during the sampling phase | BAYES | NCHAIN= |
| 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 MCMC diagnostics for each Markov chain | BAYES | DIAGNOSTICS(BYCHAIN)= |
| 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= |
| Displays posterior summary statistics for each Markov chain | BAYES | STATISTICS(BYCHAIN)= |
| 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() |
| Endogenous Variable Options | ||
| Specifies a discrete variable | ENDOGENOUS | DISCRETE() |
| Specifies a censored variable | ENDOGENOUS | CENSORED() |
| Specifies a truncated variable | ENDOGENOUS | TRUNCATED() |
| Specifies a stochastic frontier variable | ENDOGENOUS | FRONTIER() |
| Heteroscedasticity Model Options | ||
| Specifies the function for heteroscedasticity models | HETERO | LINK= |
| Squares the function for heteroscedasticity models | HETERO | SQUARE |
| Specifies no constant for heteroscedasticity models | HETERO | NOCONST |
| Output Control Options | ||
| Specifies the ODS tables to display | DISPLAY | |
| Specifies the ODS tables to save as output tables | DISPLAYOUT | |
| Outputs the predicted values | OUTPUT | PREDICTED |
| Outputs the structured part | OUTPUT | XBETA |
| Outputs the residuals | OUTPUT | RESIDUAL |
| Outputs the error standard deviation | OUTPUT | ERRSTD |
| Outputs the marginal effects | OUTPUT | MARGINAL |
| Outputs the probability for the current response | OUTPUT | PROB |
| Outputs the probability for all responses | OUTPUT | PROBALL |
| Outputs the expected value | OUTPUT | EXPECTED |
| Outputs the conditional expected value | OUTPUT | CONDITIONAL |
| Outputs the inverse Mills ratio | OUTPUT | MILLS |
| Outputs the technical efficiency measures | OUTPUT | TE1 |
| OUTPUT | TE2 | |
| Test Request Options | ||
| Requests Wald, Lagrange multiplier, and likelihood ratio tests | TEST | ALL |
| Requests the Wald test | TEST | WALD |
| Requests the Lagrange multiplier test | TEST | LM |
| Requests the likelihood ratio test | TEST | LR |
Last updated: July 09, 2026