Features |
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