Directional multivariate extremes in environmental phenomena

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dc.citation.journalTitleEnvironmetricseng
dc.contributor.authorTorres, R.
dc.contributor.authorDe michele, C.
dc.contributor.authorLaniado, H.
dc.contributor.authorLillo, R.E.
dc.contributor.departmentUniversidad EAFIT. Escuela de Cienciasspa
dc.contributor.researchgroupModelado Matemáticospa
dc.date.accessioned2021-04-12T14:07:13Z
dc.date.available2021-04-12T14:07:13Z
dc.date.issued2017-03-01
dc.description.abstractSeveral environmental phenomena can be described by different correlated variables that must be considered jointly in order to be more representative of the nature of these phenomena. For such events, identification of extremes is inappropriate if it is based on marginal analysis. Extremes have usually been linked to the notion of quantile, which is an important tool to analyze risk in the univariate setting. We propose to identify multivariate extremes and analyze environmental phenomena in terms of the directional multivariate quantile, which allows us to analyze the data considering all the variables implied in the phenomena, as well as look at the data in interesting directions that can better describe an environmental catastrophe. Because there are many references in the literature that propose extremes detection based on copula models, we also generalize the copula method by introducing the directional approach. Advantages and disadvantages of the nonparametric proposal that we introduce and the copula methods are provided in the paper. We show with simulated and real data sets how by considering the first principal component direction we can improve the visualization of extremes. Finally, two cases of study are analyzed: a synthetic case of flood risk at a dam (a three-variable case) and a real case study of sea storms (a five-variable case). Copyright © 2017 John Wiley & Sons, Ltd.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=6258
dc.identifier.doi10.1002/env.2428
dc.identifier.issn11804009
dc.identifier.issn1099095X
dc.identifier.otherWOS;000397270000005
dc.identifier.otherSCOPUS;2-s2.0-85010500315
dc.identifier.urihttp://hdl.handle.net/10784/27782
dc.language.isoengeng
dc.publisherJohn Wiley and Sons Ltd
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85010500315&doi=10.1002%2fenv.2428&partnerID=40&md5=e2793834e28acb2c411cceb8c5d91c14
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1180-4009
dc.sourceEnvironmetrics
dc.subject.keywordcatastrophic eventeng
dc.subject.keyworddameng
dc.subject.keywordenvironmental assessmenteng
dc.subject.keywordextreme eventeng
dc.subject.keywordfloodeng
dc.subject.keywordliterature revieweng
dc.subject.keywordmarine environmenteng
dc.subject.keywordmultivariate analysiseng
dc.subject.keywordnumerical modeleng
dc.subject.keywordprincipal component analysiseng
dc.subject.keywordrisk assessmenteng
dc.subject.keywordstormeng
dc.subject.keywordvisualizationeng
dc.titleDirectional multivariate extremes in environmental phenomenaeng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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