The HPQLIM Procedure

Functional Summary

Table 4.1 summarizes the statements and options used with the HPQLIM procedure.

Table 4.1: HPQLIM Functional Summary

Description

Statement

Option

Data Set Options

   

Specifies the input data set

HPQLIM

DATA=

Writes parameter estimates to an output data set

HPQLIM

OUTEST=

Writes predictions to an output data set

OUTPUT

OUT=

Declaring the Role of Variables

   

Specifies a frequency variable

FREQ

 

Specifies a weight variable

WEIGHT

NONORMALIZE

Printing Control Options

   

Requests all printing options

HPQLIM

PRINTALL

Prints the correlation matrix of the estimates

HPQLIM

CORRB

Prints the covariance matrix of the estimates

HPQLIM

COVB

Suppresses the normal printed output

HPQLIM

NOPRINT

Plotting Options

   

Displays plots

HPQLIM

PLOTS=

Optimization Process Control Options

   

Selects the iterative minimization method to use

HPQLIM

METHOD=

Specifies the maximum number of iterations allowed

HPQLIM

MAXITER=

Specifies the maximum number of function calls

HPQLIM

MAXFUNC=

Specifies the upper limit of CPU time in seconds

HPQLIM

MAXTIME=

Specifies an absolute convergence criterion

HPQLIM

ABSCONV=

Specifies an absolute function convergence criterion

HPQLIM

ABSFCONV=

Specifies an absolute gradient convergence criterion

HPQLIM

ABSGCONV=

Specifies a relative function convergence criterion

HPQLIM

FCONV=

Specifies a relative gradient convergence criterion

HPQLIM

GCONV=

Specifies an absolute parameter convergence criterion

HPQLIM

ABSXCONV=

Specifies a matrix singularity criterion

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

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 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 the expected value

OUTPUT

EXPECTED

Outputs the conditional expected value

OUTPUT

CONDITIONAL

Outputs technical efficiency measures

OUTPUT

TE1

 

OUTPUT

TE2

Includes covariances in the OUTEST= data set

HPQLIM

COVOUT

Includes correlations in the OUTEST= data set

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