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Dependence modelling for spatial extremes

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Dependence modelling for spatial extremes. / Wadsworth, Jennifer; Tawn, Jon.
In: Biometrika, Vol. 99, No. 2, 06.2012, p. 253-272.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Wadsworth J, Tawn J. Dependence modelling for spatial extremes. Biometrika. 2012 Jun;99(2):253-272. doi: 10.1093/biomet/asr080

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Wadsworth, Jennifer ; Tawn, Jon. / Dependence modelling for spatial extremes. In: Biometrika. 2012 ; Vol. 99, No. 2. pp. 253-272.

Bibtex

@article{90bfb448f9b34a79a1b0d4fbdc2602ab,
title = "Dependence modelling for spatial extremes",
abstract = "Current dependence models for spatial extremes are based upon max-stable processes. Within this class, there are few inferentially viable models available, and we propose one further model. More problematic are the restrictive assumptions that must be made when using max-stable processes to model dependence for spatial extremes: it must be assumed that the dependence structure of the observed extremes is compatible with a limiting model that holds for all events more extreme than those that have already occurred. This problem has long been acknowledged in the context of finite-dimensional multivariate extremes, in particular when data display dependence at observable levels, but are independent in the limit. We propose a flexible class of models that is suitable for such data in a spatial context. In addition, we consider the situation where the extremal dependence structure may vary with distance. We apply our models to spatially referenced significant wave height data from the North Sea, finding evidence that their extremal structure is not compatible with a limiting dependence model.",
keywords = "Asymptotic independence , Extremal dependence , Max-stable process, Significant wave height , Spatial extreme value theory",
author = "Jennifer Wadsworth and Jon Tawn",
year = "2012",
month = jun,
doi = "10.1093/biomet/asr080",
language = "English",
volume = "99",
pages = "253--272",
journal = "Biometrika",
issn = "0006-3444",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Dependence modelling for spatial extremes

AU - Wadsworth, Jennifer

AU - Tawn, Jon

PY - 2012/6

Y1 - 2012/6

N2 - Current dependence models for spatial extremes are based upon max-stable processes. Within this class, there are few inferentially viable models available, and we propose one further model. More problematic are the restrictive assumptions that must be made when using max-stable processes to model dependence for spatial extremes: it must be assumed that the dependence structure of the observed extremes is compatible with a limiting model that holds for all events more extreme than those that have already occurred. This problem has long been acknowledged in the context of finite-dimensional multivariate extremes, in particular when data display dependence at observable levels, but are independent in the limit. We propose a flexible class of models that is suitable for such data in a spatial context. In addition, we consider the situation where the extremal dependence structure may vary with distance. We apply our models to spatially referenced significant wave height data from the North Sea, finding evidence that their extremal structure is not compatible with a limiting dependence model.

AB - Current dependence models for spatial extremes are based upon max-stable processes. Within this class, there are few inferentially viable models available, and we propose one further model. More problematic are the restrictive assumptions that must be made when using max-stable processes to model dependence for spatial extremes: it must be assumed that the dependence structure of the observed extremes is compatible with a limiting model that holds for all events more extreme than those that have already occurred. This problem has long been acknowledged in the context of finite-dimensional multivariate extremes, in particular when data display dependence at observable levels, but are independent in the limit. We propose a flexible class of models that is suitable for such data in a spatial context. In addition, we consider the situation where the extremal dependence structure may vary with distance. We apply our models to spatially referenced significant wave height data from the North Sea, finding evidence that their extremal structure is not compatible with a limiting dependence model.

KW - Asymptotic independence

KW - Extremal dependence

KW - Max-stable process

KW - Significant wave height

KW - Spatial extreme value theory

U2 - 10.1093/biomet/asr080

DO - 10.1093/biomet/asr080

M3 - Journal article

VL - 99

SP - 253

EP - 272

JO - Biometrika

JF - Biometrika

SN - 0006-3444

IS - 2

ER -