Modeling extreme values of processes observed at irregular time steps: application to significant wave height
This work is motivated by the analysis of the extremal behavior of buoy and satellite data describing wave conditions in the North Atlantic Ocean. The available data sets consist of time series of significant wave height (Hs) with irregular time sampling. In such a situation, the usual statistical m...
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ftunivhongkonghu:oai:hub.hku.hk:10722/193216 2023-05-15T17:29:54+02:00 Modeling extreme values of processes observed at irregular time steps: application to significant wave height Raillard, N Ailliot, P Yao, J 2014 http://hdl.handle.net/10722/193216 eng eng Institute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/ United States Annals of Applied Statistics Annals of Applied Statistics, 2014, v. 8 n. 1, p. 1-647 647 227057 1932-6157 1 http://hdl.handle.net/10722/193216 8 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. CC-BY-NC-ND Article 2014 ftunivhongkonghu 2023-01-14T15:59:57Z This work is motivated by the analysis of the extremal behavior of buoy and satellite data describing wave conditions in the North Atlantic Ocean. The available data sets consist of time series of significant wave height (Hs) with irregular time sampling. In such a situation, the usual statistical methods for analyzing extreme values cannot be used directly. The method proposed in this paper is an extension of the peaks over threshold (POT) method, where the distribution of a process above a high threshold is approximated by a max-stable process whose parameters are estimated by maximizing a composite likelihood function. The efficiency of the proposed method is assessed on an extensive set of simulated data. It is shown, in particular, that the method is able to describe the extremal behavior of several common time series models with regular or irregular time sampling. The method is then used to analyze Hs data in the North Atlantic Ocean. The results indicate that it is possible to derive realistic estimates of the extremal properties of Hs from satellite data, despite its complex space–time sampling. postprint Article in Journal/Newspaper North Atlantic University of Hong Kong: HKU Scholars Hub |
institution |
Open Polar |
collection |
University of Hong Kong: HKU Scholars Hub |
op_collection_id |
ftunivhongkonghu |
language |
English |
description |
This work is motivated by the analysis of the extremal behavior of buoy and satellite data describing wave conditions in the North Atlantic Ocean. The available data sets consist of time series of significant wave height (Hs) with irregular time sampling. In such a situation, the usual statistical methods for analyzing extreme values cannot be used directly. The method proposed in this paper is an extension of the peaks over threshold (POT) method, where the distribution of a process above a high threshold is approximated by a max-stable process whose parameters are estimated by maximizing a composite likelihood function. The efficiency of the proposed method is assessed on an extensive set of simulated data. It is shown, in particular, that the method is able to describe the extremal behavior of several common time series models with regular or irregular time sampling. The method is then used to analyze Hs data in the North Atlantic Ocean. The results indicate that it is possible to derive realistic estimates of the extremal properties of Hs from satellite data, despite its complex space–time sampling. postprint |
format |
Article in Journal/Newspaper |
author |
Raillard, N Ailliot, P Yao, J |
spellingShingle |
Raillard, N Ailliot, P Yao, J Modeling extreme values of processes observed at irregular time steps: application to significant wave height |
author_facet |
Raillard, N Ailliot, P Yao, J |
author_sort |
Raillard, N |
title |
Modeling extreme values of processes observed at irregular time steps: application to significant wave height |
title_short |
Modeling extreme values of processes observed at irregular time steps: application to significant wave height |
title_full |
Modeling extreme values of processes observed at irregular time steps: application to significant wave height |
title_fullStr |
Modeling extreme values of processes observed at irregular time steps: application to significant wave height |
title_full_unstemmed |
Modeling extreme values of processes observed at irregular time steps: application to significant wave height |
title_sort |
modeling extreme values of processes observed at irregular time steps: application to significant wave height |
publisher |
Institute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/ |
publishDate |
2014 |
url |
http://hdl.handle.net/10722/193216 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
Annals of Applied Statistics Annals of Applied Statistics, 2014, v. 8 n. 1, p. 1-647 647 227057 1932-6157 1 http://hdl.handle.net/10722/193216 8 |
op_rights |
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
op_rightsnorm |
CC-BY-NC-ND |
_version_ |
1766125134897217536 |