Robust regression estimators compared via monte carlo

Abstract

This paper presents results of a Monte Carlo simulation of eight families of robust regression estimators in various situations. The effects studied include long-tailed error terms, measurement error in the independent variables, various spacings of the independent variables, different sample sizes and correlation between the independent variables. An estimator that combines the best features of several of the estimators is recommended for further study.