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Article: Modeling extreme values of processes observed at irregular time steps: application to significant wave height

TitleModeling extreme values of processes observed at irregular time steps: application to significant wave height
Authors
Issue Date2014
PublisherInstitute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/
Citation
Annals of Applied Statistics, 2014, v. 8 n. 1, p. 1-647 How to Cite?
AbstractThis 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.
Persistent Identifierhttp://hdl.handle.net/10722/193216
ISSN
2015 Impact Factor: 1.432
2015 SCImago Journal Rankings: 1.533

 

DC FieldValueLanguage
dc.contributor.authorRaillard, Nen_US
dc.contributor.authorAilliot, Pen_US
dc.contributor.authorYao, Jen_US
dc.date.accessioned2013-12-20T02:37:06Z-
dc.date.available2013-12-20T02:37:06Z-
dc.date.issued2014-
dc.identifier.citationAnnals of Applied Statistics, 2014, v. 8 n. 1, p. 1-647en_US
dc.identifier.issn1932-6157-
dc.identifier.urihttp://hdl.handle.net/10722/193216-
dc.description.abstractThis 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.-
dc.languageengen_US
dc.publisherInstitute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/-
dc.relation.ispartofAnnals of Applied Statisticsen_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleModeling extreme values of processes observed at irregular time steps: application to significant wave heighten_US
dc.typeArticleen_US
dc.identifier.emailYao, J: jeffyao@hku.hken_US
dc.identifier.authorityYao, JJ=rp01473en_US
dc.description.naturepostprint-
dc.identifier.hkuros227057en_US
dc.identifier.volume8-
dc.identifier.issue1-
dc.identifier.spage1-
dc.identifier.epage647-
dc.publisher.placeUnited States-

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