The proposal ofMestimators for regression (Huber, 1973) and the
development of an algorithm for its computation (Dutter, 1977) has lead to an
increased activity for further research in this area. New regression estimators
were introduced that combine a high level of robustness with high efficiency.
Also fast algorithms have been developed and implemented in several software
packages. We provide a review of the most important methods, and
compare the performance of the algorithms implemented in R .