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 ∈ 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. © 1993 Academic Press, Inc.
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Einmahl, J. H. J., De Haan, L., & Huang, X. (1993). Estimating a multidimensional extreme-value distribution. Journal of Multivariate Analysis, 47(1), 35–47. https://doi.org/10.1006/jmva.1993.1069
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