REG Procedure
The REG procedure is a general purpose procedure for ordinary least squares regression. The following
are highlights of the REG procedure's features:
- supports multiple MODEL statements
- provides nine model-selection methods
- allows interactive changes both in the model and the data used to fit the model
- supports linear equality restrictions on parameters
- provides tests of linear hypotheses and multivariate hypotheses
- provides collinearity diagnostics
- computes predicted values, residuals, studentized residuals, confidence limits, and influence statistics
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- allows correlation or crossproduct input
- saves requested statistics to SAS data sets
- enables you to save the fitted model to an item store, which can be processed by the PLM procedure
- performs BY group processing, which enables you to obtain separate analyses on grouped observations
- perform weighted estimation
- create a SAS data set that corresponds to any output table
- automatically creates graphs by using ODS Graphics
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For further details see the REG Procedure
Examples