Generalized additive modelling of sample extremes

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Version: Final published version
Serval ID
serval:BIB_0C0E2BCFB4C9
Type
Article: article from journal or magazin.
Collection
Publications
Title
Generalized additive modelling of sample extremes
Journal
Journal of the Royal Statistical Society; Series C (Applied Statistics)
Author(s)
Chavez-Demoulin V., Davison A. C.
ISSN
0035-9254
Publication state
Published
Issued date
01/2005
Peer-reviewed
Oui
Volume
54
Number
1
Pages
207-222
Language
english
Abstract
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.
Keywords
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
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23/08/2011 7:59
Last modification date
20/08/2019 12:33
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