The ROBUSTREG Procedure
The following statements are available in the ROBUSTREG procedure:
PROC ROBUSTREG
<options> ;
BY
variables ;
CLASS
variables ;
EFFECT
name=effect-type(variables </ options>) ;
ID
variables ;
MODEL
response = <effects> </ options> ;
OUTPUT
<OUT=SAS-data-set> keyword=name <…keyword=name> ;
PERFORMANCE
<options> ;
TEST
effects ;
WEIGHT
variable ;
The PROC ROBUSTREG statement invokes the procedure. The METHOD= option in the PROC ROBUSTREG statement selects one of the four estimation methods, M, LTS, S, and MM. By default, Huber M estimation is used. The MODEL statement is required and specifies the variables to be used in the regression. You can specify main effects and interaction terms in the MODEL statement, as in the GLM procedure. (See Chapter 44: The GLM Procedure.) The CLASS statement specifies which explanatory variables to treat as categorical. The ID statement names variables to identify observations in the outlier diagnostics tables. The WEIGHT statement identifies a variable in the input data set whose values are used to weight the observations. The OUTPUT statement creates an output data set that contains final weights, predicted values, and residuals. The TEST statement requests robust linear tests for the model parameters. The PERFORMANCE statement tunes the performance of the procedure by using single or multiple processors available on the hardware. Multiple OUTPUT and TEST statements are permitted.