The HPQLIM Procedure
Functional Summary
Table 1 summarizes the statements and options used with the HPQLIM procedure.
Table 1: PROC HPQLIM Functional Summary
| Description | Statement | Option |
|---|---|---|
| Data Set Options | ||
| Specifies the input data set | PROC HPQLIM | DATA= |
| Writes parameter estimates to an output data set | PROC HPQLIM | OUTEST= |
| Writes predictions to an output data set | OUTPUT | OUT= |
| Declaring the Role of Variables | ||
| Specifies BY-group processing | BY | |
| Specifies a frequency variable | FREQ | |
| Specifies a weight variable | WEIGHT | NONORMALIZE |
| Printing Control Options | ||
| Requests all printing options | PROC HPQLIM | PRINTALL |
| Prints the correlation matrix of the estimates | PROC HPQLIM | CORRB |
| Prints the covariance matrix of the estimates | PROC HPQLIM | COVB |
| Suppresses the normal printed output | PROC HPQLIM | NOPRINT |
| Plotting Options | ||
| Displays plots | PROC HPQLIM | PLOTS= |
| Optimization Process Control Options | ||
| Selects the iterative minimization method to use | PROC HPQLIM | METHOD= |
| Specifies the maximum number of iterations allowed | PROC HPQLIM | MAXITER= |
| Specifies the maximum number of function calls | PROC HPQLIM | MAXFUNC= |
| Specifies the upper limit of CPU time in seconds | PROC HPQLIM | MAXTIME= |
| Specifies an absolute convergence criterion | PROC HPQLIM | ABSCONV= |
| Specifies an absolute function convergence criterion | PROC HPQLIM | ABSFCONV= |
| Specifies an absolute gradient convergence criterion | PROC HPQLIM | ABSGCONV= |
| Specifies a relative function convergence criterion | PROC HPQLIM | FCONV= |
| Specifies a relative gradient convergence criterion | PROC HPQLIM | GCONV= |
| Specifies an absolute parameter convergence criterion | PROC HPQLIM | ABSXCONV= |
| Specifies a matrix singularity criterion | PROC HPQLIM | SINGULAR= |
| Sets boundary restrictions on parameters | BOUNDS | |
| Sets initial values for parameters | INIT | |
| Sets linear restrictions on parameters | RESTRICT | |
| Model Estimation Options | ||
| Suppresses the intercept parameter | MODEL | NOINT |
| Specifies the method to calculate parameter covariance | PROC HPQLIM | COVEST= |
| Bayesian MCMC Options | ||
| Specifies the initial values of the MCMC | INIT | |
| Specifies the maximum number of tuning phases | BAYES | MAXTUNE= |
| Specifies the minimum number of tuning phases | BAYES | MINTUNE= |
| Specifies the number of burn-in iterations | BAYES | NBI= |
| Specifies the number of iterations during the sampling phase | BAYES | NMC= |
| Specifies the number of iterations during the tuning phase | BAYES | NTU= |
| Controls options for constructing the initial proposal covariance matrix | BAYES | PROPCOV |
| Specifies the sampling scheme | BAYES | SAMPLING= |
| Specifies the random number generator seed | BAYES | SEED= |
| Controls the thinning of the Markov chain | BAYES | THIN= |
| Bayesian Summary Statistics and Convergence Diagnostic Options | ||
| Displays convergence diagnostics | BAYES | DIAGNOSTICS= |
| Displays summary statistics of the posterior samples | BAYES | STATISTICS= |
| Bayesian Prior and Posterior Sample Options | ||
| Specifies a SAS data set for the posterior samples | BAYES | OUTPOST= |
| Bayesian Analysis Options | ||
| Specifies the normal prior distribution | PRIOR | NORMAL(MEAN=, VAR=) |
| Specifies the gamma prior distribution | PRIOR | GAMMA(SHAPE=, SCALE=) |
| Specifies the inverse gamma prior distribution | PRIOR | IGAMMA(SHAPE=, SCALE=) |
| Specifies the uniform prior distribution | PRIOR | UNIFORM(MIN=, MAX=) |
| Specifies the beta prior distribution | PRIOR |
BETA(SHAPE1=, SHAPE2=, MIN=, MAX=) |
| Specifies the t prior distribution | PRIOR | T(LOCATION=, DF=) |
| 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 | ||
| Outputs predicted values | OUTPUT | PREDICTED |
| Outputs the structured part | OUTPUT | XBETA |
| Outputs residuals | OUTPUT | RESIDUAL |
| Outputs the error standard deviation | OUTPUT | ERRSTD |
| Outputs marginal effects | OUTPUT | MARGINAL |
| Outputs probability for the current response | OUTPUT | PROB |
| Outputs probability for all responses | OUTPUT | PROBALL |
| Outputs the expected value | OUTPUT | EXPECTED |
| Outputs the conditional expected value | OUTPUT | CONDITIONAL |
| Outputs inverse Mills ratio | OUTPUT | MILLS |
| Outputs technical efficiency measures | OUTPUT | TE1 |
| OUTPUT | TE2 | |
| Includes covariances in the OUTEST= data set | PROC HPQLIM | COVOUT |
| Includes correlations in the OUTEST= data set | PROC HPQLIM | CORROUT |
| 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: January 07, 2025