Abstract
A problem with robust regression estimators is that the tuning constants need to be chosen for the estimators to be completely specified. Here an adaptive method is used to choose the tuning constant and to investigate its variability. The effects that this has on the behaviour of the parameter estimates is also investigated. Using the jackknife the asymptotic mean-squared error of the estimators is estimated and the tuning constant is chosen to minimize this. The Huber and Tukey robust regression estimators are explored by using different error distributions.
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