The main features of the ROBUSTREG procedure are as follows:

• offers four estimation methods: M, LTS, S, and MM

• provides 10 weight functions for M estimation

• provides robust R-square and deviance for all estimates

• provides asymptotic covariance and confidence intervals for regression parameter with the M, S, and MM methods

• provides robust Wald and F tests for regression parameters with the M and MM methods

• provides Mahalanobis distance and robust Mahalanobis distance with generalized minimum covariance determinant (MCD) algorithm

• provides outlier and leverage-point diagnostics

• supports parallel computing for S and LTS estimates

• supports constructed effects including spline and multimember effects

• produces fit plots and diagnostic plots by using ODS Graphics