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research article

Spectral Density Ratio Models for Multivariate Extremes

De Carvalho, Miguel  
•
Davison, Anthony C.  
2014
Journal Of The American Statistical Association

The modeling of multivariate extremes has received increasing recent attention because of its importance in risk assessment. In classical statistics of extremes, the joint distribution of two or more extremes has a nonparametric form, subject to moment constraints. This article develops a semiparametric model for the situation where several multivariate extremal distributions are linked through the action of a covariate on an unspecified baseline distribution, through a so-called density ratio model. Theoretical and numerical aspects of empirical likelihood inference for this model are discussed, and an application is given to pairs of extreme forest temperatures. Supplementary materials for this article are available online.

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Type
research article
DOI
10.1080/01621459.2013.872651
Web of Science ID

WOS:000338236000025

Author(s)
De Carvalho, Miguel  
Davison, Anthony C.  
Date Issued

2014

Publisher

American Statistical Association

Published in
Journal Of The American Statistical Association
Volume

109

Issue

506

Start page

764

End page

776

Subjects

Air temperature

•

Empirical likelihood

•

Exponential tilting

•

Forest microclimate

•

Multivariate extreme values

•

Semiparametric modeling

•

Spectral distribution

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
STAT  
Available on Infoscience
August 29, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/106470
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