Abstract
This chapter explores analogs of linear combinations of order statistics in the linear model and presents a few results. It highlights the problem of estimating the regression parameters of a linear model as the number of observations becomes large and the number of regression parameters remains fixed. Two classes of procedures have attracted particular attention in this problem (M) (maximum likelihood type) estimates and linear combinations of order statistics. A third class, estimates based on rank tests, also exists. The chapter discusses the extent to which the relatively weak conditions for the asymptotic theory of linear combinations or order statistics suffice in the more general case.
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