Robust Estimation OLS is not robust to outliers. It is computed by minimizing the sum of squares of the residuals and each outlying observation has a large residual and consequently a large effect on this sum of squares. On the other hand, The M-estimators used in robust statistics (Heritier et al. 2009; Huber 1964; Maronna, Martin, and Yohai 2006) are not influenced by outlying data. Huber (1964) proposed to minimize functions which are less influenced by outliers rather than the sum of squares.