The QLIM Procedure
- Overview
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Getting Started
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Syntax
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DetailsOrdinal Discrete Choice ModelingLimited Dependent Variable ModelsStochastic Frontier Production and Cost ModelsHeteroscedasticity and Box-Cox TransformationBivariate Limited Dependent Variable ModelingSelection ModelsMultivariate Limited Dependent ModelsVariable SelectionTests on ParametersBayesian AnalysisPrior DistributionsOutput to SAS Data SetOUTEST= Data SetNamingODS Table NamesODS Graphics
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Examples
- References
BOUNDS Statement
BOUNDS bound1 < , bound2 …> ;
The BOUNDS statement imposes simple boundary constraints on the parameter estimates. BOUNDS statement constraints refer to the parameters estimated by the QLIM procedure. Any number of BOUNDS statements can be specified.
Each bound is composed of parameters and constants and inequality operators. Parameters associated with regressor variables are referred to by the names of the corresponding regressor variables:
item operator item < operator item < operator item …> >
Each item is a constant, the name of a parameter, or a list of parameter names. See the section Naming of Parameters for more details on how parameters are named in the QLIM procedure. Each operator is ’<’, ’>’, ’<=’, or ’>=’.
Both the BOUNDS statement and the RESTRICT statement can be used to impose boundary constraints; however, the BOUNDS statement provides a simpler syntax for specifying these kinds of constraints. See the RESTRICT Statement for more information.
The following BOUNDS statement constrains the estimates of the parameters associated with the variable ttime and the variables x1 through x10 to be between 0 and 1. This example illustrates the use of parameter lists to specify boundary constraints.
bounds 0 < ttime x1-x10 < 1;
The following BOUNDS statement constrains the estimates of the correlation (_RHO) and sigma (_SIGMA) in the bivariate model:
bounds _rho >= 0, _sigma.y1 > 1, _sigma.y2 < 5;
The BOUNDS statement is not supported if a BAYES statement is also specified. In Bayesian analysis, the restrictions on parameters are usually introduced through the prior distribution.