Generalized additive modelling of sample extremes

Détails

Ressource 1Demande d'une copieTélécharger: BIB_0C0E2BCFB4C9.P001.pdf (341.11 [Ko])
Etat: Supprimée
Version: Final published version
ID Serval
serval:BIB_0C0E2BCFB4C9
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Generalized additive modelling of sample extremes
Périodique
Journal of the Royal Statistical Society; Series C (Applied Statistics)
Auteur(s)
Chavez-Demoulin V., Davison A. C.
ISSN
0035-9254
Statut éditorial
Publié
Date de publication
01/2005
Peer-reviewed
Oui
Volume
54
Numéro
1
Pages
207-222
Langue
anglais
Résumé
We describe smooth non-stationary generalized additive modelling for sample extremes, in which spline smoothers are incorporated into models for exceedances over high thresholds. Fitting is by maximum penalized likelihood estimation, with uncertainty assessed by using differences of deviances and bootstrap simulation. The approach is illustrated by using data on extreme winter temperatures in the Swiss Alps, analysis of which shows strong influence of the north Atlantic oscillation. Benefits of the new approach are flexible and appropriate modelling of extremes, more realistic assessment of estimation uncertainty and the accommodation of complex dependence patterns.
Mots-clé
bootstrap, generalized additive model, generalized Pareto distribution, natural cubic spline, North Atlantic oscillation, parameter orthogonality, peaks over threshold, penalized likelihood, satistics of extremes, temperature data
Web of science
Création de la notice
23/08/2011 7:59
Dernière modification de la notice
20/08/2019 12:33
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