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Estimating a Multidimensional Extreme-Value Distribution

By J.H.J. Einmahl, L. Dehaan and X. Huang


AbstractLet 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 ∈ N, 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

Publisher: Academic Press.
Year: 1993
DOI identifier: 10.1006/jmva.1993.1069
OAI identifier:

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