The GLMSELECT Procedure
-
Overview
- Getting Started
-
Syntax
-
DetailsModel-Selection MethodsModel Selection IssuesCriteria Used in Model Selection MethodsCLASS Variable Parameterization and the SPLIT OptionMacro Variables Containing Selected ModelsUsing the STORE StatementBuilding the SSCP MatrixModel AveragingUsing Validation and Test DataCross ValidationExternal Cross ValidationScreeningDisplayed OutputODS Table NamesODS Graphics
-
Examples
- References
A WEIGHT statement names a variable in the input data set with values that are relative weights for a weighted least squares fit. If the weight value is proportional to the reciprocal of the variance for each observation, then the weighted estimates are the best linear unbiased estimates (BLUE).
Values of the weight variable must be nonnegative. If an observation’s weight is zero, the observation is deleted from the analysis. If a weight is negative or missing, it is set to zero, and the observation is excluded from the analysis. A more complete description of the WEIGHT statement can be found in Chapter 45: The GLM Procedure.