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arXiv · 1403.1975

An M-estimator of spatial tail dependence

John Einmahl·Anna Kiriliouk·Andrea Krajina·Johan Segers
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Abstract

Tail dependence models for distributions attracted to a max-stable law are fitted using observations above a high threshold. To cope with spatial, high-dimensional data, a rank-based M-estimator is proposed relying on bivariate margins only. A data-driven weight matrix is used to minimize the asymptotic variance. Empirical process arguments show that the estimator is consistent and asymptotically normal. Its finite-sample performance is assessed in simulation experiments involving popular max-stable processes perturbed with additive noise. An analysis of wind speed data from the Netherlands illustrates the method.

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John Einmahl, Anna Kiriliouk, Andrea Krajina, Johan Segers. 2014-03-08. An M-estimator of spatial tail dependence. https://arxiv.org/abs/1403.1975

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