A weighted dispersion function for estimation in linear models

Robust estimates for the parameters in the general linear model are proposed which are based on weighted rank statistics. The method is based on the minimization of a dispersion function defined by a weighted Gini's mean difference. An asymptotic distribution of the estimate is derived. Some examples are discussed which point out that the ranking can be based on a restricted set of comparisons and still retain high efficiency. (Author)