The ROBUSTREG Procedure


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