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Spatial extremes: Models for the stationary case

2006/02/01 by Laurens de Haan, Teresa T. Pereira · 3 citations
Economics, Econometrics and Finance · Mathematics · #Financial Risk and Volatility Modeling #Point processes and geometric inequalities #Spatial and Panel Data Analysis #math.ST #msc:60G10 #msc:60G70 #msc:62E20 #msc:62G32 #msc:62H11 #msc:62M40 #stat.TH

paper · pdf · doi:10.1214/009053605000000886

published as Annals of Statistics 2006, Vol. 34, No. 1, 146-168 · Published at http://dx.doi.org/10.1214/009053605000000886 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

openalex publication_date 2006/02/01 · arxiv created 2006/05/16 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

The aim of this paper is to provide models for spatial extremes in the case of stationarity. The spatial dependence at extreme levels of a stationary process is modeled using an extension of the theory of max-stable processes of de Haan and Pickands [Probab. Theory Related Fields 72 (1986) 477–492]. We propose three one-dimensional and three two-dimensional models. These models depend on just one parameter or a few parameters that measure the strength of tail dependence as a function of the distance between locations. We also propose two estimators for this parameter and prove consistency under domain of attraction conditions and asymptotic normality under appropriate extra conditions.

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