Estimating a multidimensional extreme-value distribution

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Abstract
Let F and G be multivariate probability distribution functions, each with equal one dimensional marginals, such that there exists a sequence of constants an > 0, n [set membership, variant] , with [formula] for all continuity points (x1, ..., xd) of G. The distribution function G is characterized by the extreme-value index (determining the marginals) and the so-called angular measure (determining the dependence structure). In this paper, a non-parametric estimator of G, based on a random sample from F, is proposed. Consistency as well as asymptotic normality are proved under certain regularity conditions. (This abstract was borrowed from another version of this item.)

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