The HPQLIM Procedure

PRIOR Statement

PRIOR _REGRESSORS |parameter-list ${\scriptstyle \sim }$ distribution ;

The PRIOR statement specifies the prior distribution of the model parameters. You must specify one parameter or a list of parameters, a tilde $\sim$ , and then a distribution with its parameters. Multiple PRIOR statements are allowed.

You can specify the following distributions:

NORMAL(MEAN= $\mu$ , VAR= $\sigma ^2$ ): specifies a normal distribution with the parameters MEAN and VAR.
GAMMA(SHAPE= $a$ , SCALE= $b$ ): specifies a gamma distribution with the parameters SHAPE and SCALE.
IGAMMA(SHAPE= $a$ , SCALE= $b$ ): specifies an inverse gamma distribution with the parameters SHAPE and SCALE.
UNIFORM(MIN= $m$ , MAX= $M$ ): specifies a uniform distribution that is defined between MIN and MAX.
BETA(SHAPE1= $a$ , SHAPE2= $b$ , MIN= $m$ , MAX= $M$ ): specifies a beta distribution with the parameters SHAPE1 and SHAPE2 and defined between MIN and MAX.
T(LOCATION= $\mu$ , DF= $\nu$ ): specifies a noncentral t distribution with DF degrees of freedom and a location parameter equal to LOCATION.

For more information about how to specify distributions, see the section Standard Distributions.

You can specify the special keyword REGRESSORS to select all the parameters that are used in the linear regression component of the model.