The HPQLIM Procedure

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=

Specifies BY-group processing

BY

Specifies a frequency variable

FREQ

Specifies a weight variable

WEIGHT

NONORMALIZE

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

Displays plots

PROC HPQLIM

PLOTS=

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

Suppresses the intercept parameter

MODEL

NOINT

Specifies the method to calculate parameter covariance

PROC HPQLIM

COVEST=

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=

Displays convergence diagnostics

BAYES

DIAGNOSTICS=

Displays summary statistics of the posterior samples

BAYES

STATISTICS=

Specifies a SAS data set for the posterior samples

BAYES

OUTPOST=

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=)

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()

Specifies the function for heteroscedasticity models

HETERO

LINK=

Squares the function for heteroscedasticity models

HETERO

SQUARE

Specifies no constant for heteroscedasticity models

HETERO

NOCONST

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

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