Performance of Robust Regression Estimators

Abstract

Ordinary least-squares (OLS) estimates for a linear model are very sensitive to unusual values in the design space or outliers among unpredicted values. Even one single value may have a large effect on the parameter estimates. This paper aims to focus, review and describe some available and popular, robustregressiontechniques, including compare them in terms of efficiency. Recent developed robust regression techniques also discussed.