Robust Regression: Computational Methods for M-Estimates.

The computation of robust M-estimates of regression is considered in detail using the Psi functions of Huber, Andrews, and Hampel. The computation of M-estimates of regression is considered for linear models, linear models with vector observations, and nonlinear models. Examples are given using actual data for each of these different classes of models. Examples are given using actual data for each of these different classes of models. Careful attention is given to the important problem of convergence of M-estimates with redescending Psi functions. A lengthy treatment of this problem is given for the Daniel and Wood data by considering several starting methods for the iterative solution and different breakpoints for the Psi functions. (Author)