Einmahl, John
[Tilburg University]
Kiriliouk, Anna
[UCL]
Krajina, Andrea
[University of Gottingen]
Segers, Johan
[UCL]
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.
Bibliographic reference |
Einmahl, John ; Kiriliouk, Anna ; Krajina, Andrea ; Segers, Johan. An M-estimator of spatial tail dependence. ISBA Discussion Paper ; 2014/08 (2014) 25 pages |
Permanent URL |
http://hdl.handle.net/2078.1/141771 |