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
OUTEST= Data Set
The OUTEST= data set contains all the parameters estimated in a MODEL statement. The OUTEST= option can be used when the PROC QLIM call contains one MODEL statement:
proc qlim data=a outest=e;
model y = x1 x2 x3;
endogenous y ~ censored(lb=0);
run;
Each parameter contains the estimate for the corresponding parameter in the corresponding model. In addition, the OUTEST= data set contains the following variables:
- _NAME_
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the name of the independent variable
- _TYPE_
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type of observation. PARM indicates the row of coefficients; STD indicates the row of standard deviations of the corresponding coefficients.
- _STATUS_
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convergence status for optimization
The rest of the columns correspond to the explanatory variables.
The OUTEST= data set contains one observation for the MODEL statement, giving the parameter estimates for that model. If the COVOUT option is specified, the OUTEST= data set includes additional observations for the MODEL statement, giving the rows of the covariance matrix of parameter estimates. For covariance observations, the value of the _TYPE_ variable is COV, and the _NAME_ variable identifies the parameter associated with that row of the covariance matrix. If the CORROUT option is specified, the OUTEST= data set includes additional observations for the MODEL statement, giving the rows of the correlation matrix of parameter estimates. For correlation observations, the value of the _TYPE_ variable is CORR, and the _NAME_ variable identifies the parameter associated with that row of the correlation matrix.