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The GLMSELECT Procedure

Overview
Features
Getting Started
Syntax
PROC GLMSELECT Statement BY Statement CLASS Statement CODE Statement EFFECT Statement FREQ Statement MODEL Statement MODELAVERAGE Statement OUTPUT Statement PARTITION Statement PERFORMANCE Statement SCORE Statement STORE Statement WEIGHT Statement
Details
Model-Selection Methods Model Selection Issues Criteria Used in Model Selection Methods CLASS Variable Parameterization and the SPLIT Option Macro Variables Containing Selected Models Using the STORE Statement Building the SSCP Matrix Model Averaging Using Validation and Test Data Cross Validation External Cross Validation Screening Displayed Output ODS Table Names ODS Graphics
Examples
Modeling Baseball Salaries Using Performance Statistics Using Validation and Cross Validation Scatter Plot Smoothing by Selecting Spline Functions Multimember Effects and the Design Matrix Model Averaging Elastic Net and External Cross Validation LASSO with Screening
References

Model-Selection Methods

Subsections:

Full Model Fitted (NONE)
Forward Selection (FORWARD)
Backward Elimination (BACKWARD)
Stepwise Selection(STEPWISE)
Least Angle Regression (LAR)
Lasso Selection (LASSO)
Adaptive LASSO Selection
Elastic Net Selection (ELASTICNET)

The model selection methods implemented in PROC GLMSELECT are specified with the SELECTION= option in the MODEL statement.

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