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...
Published in: | Journal of the Royal Statistical Society: Series C (Applied Statistics) |
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Online Access: | https://doi.org/10.1111/j.1467-9876.2005.00479.x |
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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 |
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Open Polar |
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RePEc (Research Papers in Economics) |
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ftrepec |
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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 |
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1 |
container_start_page |
207 |
op_container_end_page |
222 |
_version_ |
1796314033551310848 |