Clustering of extreme events created by multiple correlated maxima

Detalhes bibliográficos
Autor(a) principal: Azevedo, D
Data de Publicação: 2016
Outros Autores: Ana Cristina Moreira Freitas, Jorge Milhazes Freitas, Rodrigues, FB
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/88276
Resumo: We consider stochastic processes arising from dynamical systems by evaluating an observable function along the orbits of the system. The novelty is that we will consider observables achieving a global maximum value (possible infinite) at multiple points with special emphasis for the case where these maximal points are correlated or bound by belonging to the same orbit of a certain chosen point. These multiple correlated maxima can be seen as a new mechanism creating clustering of extreme observations, i.e., the occurrence of several extreme observations concentrated in the time frame. We recall that clustering was intimately connected with periodicity when the maximum was achieved at a single point. We will study this mechanism for creating clustering and will address the existence of limiting Extreme Value Laws, the repercussions on the value of the Extremal Index, the impact on the limit of Rare Events Points Processes, the influence on clustering patterns and the competition of domains of attraction. We also consider briefly and for comparison purposes multiple uncorrelated maxima. The systems considered include expanding maps of the interval such as Rychlik maps but also maps with an indifferent fixed point such as Manneville Pomeau maps.
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spelling Clustering of extreme events created by multiple correlated maximaWe consider stochastic processes arising from dynamical systems by evaluating an observable function along the orbits of the system. The novelty is that we will consider observables achieving a global maximum value (possible infinite) at multiple points with special emphasis for the case where these maximal points are correlated or bound by belonging to the same orbit of a certain chosen point. These multiple correlated maxima can be seen as a new mechanism creating clustering of extreme observations, i.e., the occurrence of several extreme observations concentrated in the time frame. We recall that clustering was intimately connected with periodicity when the maximum was achieved at a single point. We will study this mechanism for creating clustering and will address the existence of limiting Extreme Value Laws, the repercussions on the value of the Extremal Index, the impact on the limit of Rare Events Points Processes, the influence on clustering patterns and the competition of domains of attraction. We also consider briefly and for comparison purposes multiple uncorrelated maxima. The systems considered include expanding maps of the interval such as Rychlik maps but also maps with an indifferent fixed point such as Manneville Pomeau maps.20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/88276eng0167-278910.1016/j.physd.2015.10.002Azevedo, DAna Cristina Moreira FreitasJorge Milhazes FreitasRodrigues, FBinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T15:56:41Zoai:repositorio-aberto.up.pt:10216/88276Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:35:38.334488Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Clustering of extreme events created by multiple correlated maxima
title Clustering of extreme events created by multiple correlated maxima
spellingShingle Clustering of extreme events created by multiple correlated maxima
Azevedo, D
title_short Clustering of extreme events created by multiple correlated maxima
title_full Clustering of extreme events created by multiple correlated maxima
title_fullStr Clustering of extreme events created by multiple correlated maxima
title_full_unstemmed Clustering of extreme events created by multiple correlated maxima
title_sort Clustering of extreme events created by multiple correlated maxima
author Azevedo, D
author_facet Azevedo, D
Ana Cristina Moreira Freitas
Jorge Milhazes Freitas
Rodrigues, FB
author_role author
author2 Ana Cristina Moreira Freitas
Jorge Milhazes Freitas
Rodrigues, FB
author2_role author
author
author
dc.contributor.author.fl_str_mv Azevedo, D
Ana Cristina Moreira Freitas
Jorge Milhazes Freitas
Rodrigues, FB
description We consider stochastic processes arising from dynamical systems by evaluating an observable function along the orbits of the system. The novelty is that we will consider observables achieving a global maximum value (possible infinite) at multiple points with special emphasis for the case where these maximal points are correlated or bound by belonging to the same orbit of a certain chosen point. These multiple correlated maxima can be seen as a new mechanism creating clustering of extreme observations, i.e., the occurrence of several extreme observations concentrated in the time frame. We recall that clustering was intimately connected with periodicity when the maximum was achieved at a single point. We will study this mechanism for creating clustering and will address the existence of limiting Extreme Value Laws, the repercussions on the value of the Extremal Index, the impact on the limit of Rare Events Points Processes, the influence on clustering patterns and the competition of domains of attraction. We also consider briefly and for comparison purposes multiple uncorrelated maxima. The systems considered include expanding maps of the interval such as Rychlik maps but also maps with an indifferent fixed point such as Manneville Pomeau maps.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-01-01T00:00:00Z
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language eng
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10.1016/j.physd.2015.10.002
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