Generalized additive modelling of sample extremes

Summary. 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 devianc...

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Published in:Journal of the Royal Statistical Society: Series C (Applied Statistics)
Main Authors: V. Chavez‐Demoulin, A. C. Davison
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Online Access:https://doi.org/10.1111/j.1467-9876.2005.00479.x
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spelling ftrepec:oai:RePEc:bla:jorssc:v:54:y:2005:i:1:p:207-222 2024-04-14T08:15:38+00:00 Generalized additive modelling of sample extremes V. Chavez‐Demoulin A. C. Davison https://doi.org/10.1111/j.1467-9876.2005.00479.x unknown https://doi.org/10.1111/j.1467-9876.2005.00479.x article ftrepec https://doi.org/10.1111/j.1467-9876.2005.00479.x 2024-03-19T10:30:14Z Summary. 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. Article in Journal/Newspaper North Atlantic North Atlantic oscillation RePEc (Research Papers in Economics) Journal of the Royal Statistical Society: Series C (Applied Statistics) 54 1 207 222
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description Summary. 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.
format Article in Journal/Newspaper
author V. Chavez‐Demoulin
A. C. Davison
spellingShingle V. Chavez‐Demoulin
A. C. Davison
Generalized additive modelling of sample extremes
author_facet V. Chavez‐Demoulin
A. C. Davison
author_sort V. Chavez‐Demoulin
title Generalized additive modelling of sample extremes
title_short Generalized additive modelling of sample extremes
title_full Generalized additive modelling of sample extremes
title_fullStr Generalized additive modelling of sample extremes
title_full_unstemmed Generalized additive modelling of sample extremes
title_sort generalized additive modelling of sample extremes
url https://doi.org/10.1111/j.1467-9876.2005.00479.x
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_relation https://doi.org/10.1111/j.1467-9876.2005.00479.x
op_doi https://doi.org/10.1111/j.1467-9876.2005.00479.x
container_title Journal of the Royal Statistical Society: Series C (Applied Statistics)
container_volume 54
container_issue 1
container_start_page 207
op_container_end_page 222
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