A new blocks estimator for the extremal index
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/86714 |
Resumo: | The occurrence of successive extreme observations can have an impact on society. In extreme value theory there are parameters to evaluate the effect of clustering of high values, such as the extremal index. The estimation of the extremal index is a recurrent theme in the literature and there are several methodologies for this purpose. The majority of existing methods depend on two parameters whose choice affects the performance of the estimators. Here we consider a new estimator depending only on one of the parameters, thus contributing to a decrease in the degree of uncertainty. A simulation study presents motivating results. An application to financial data will also be presented. |
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A new blocks estimator for the extremal indexExtreme value theoryStationary sequencesDependence conditionsExtremal indextail dependencePrimarySecondaryPrimary: 60G70Secondary: 62G32Ciências Naturais::MatemáticasScience & TechnologyÁgua potável e saneamentoThe occurrence of successive extreme observations can have an impact on society. In extreme value theory there are parameters to evaluate the effect of clustering of high values, such as the extremal index. The estimation of the extremal index is a recurrent theme in the literature and there are several methodologies for this purpose. The majority of existing methods depend on two parameters whose choice affects the performance of the estimators. Here we consider a new estimator depending only on one of the parameters, thus contributing to a decrease in the degree of uncertainty. A simulation study presents motivating results. An application to financial data will also be presented.The first author was partially supported by the research unit Center of Mathematics and Applications of University of Beira Interior UIDB/00212/2020 -FCT (Fundacao para a Ciencia e a Tecnologia). The second author was financed by Portuguese Funds through FCT -Fundacao para a Ciencia e a Tecnologia within the Projects UIDB/00013/2020 and UIDP/00013/2020 of Center of Mathematics of the University of Minho, UIDB/00006/2020 and UIDP/00006/2020 of Center of Statistics and its Applications of University of Lisbon, UIDB/04621/2020 and UIDP/04621/2020 of Center for Computational and Stochastic Mathematics and PTDC/MAT-STA/28243/2017.Taylor & FrancisUniversidade do MinhoFerreira, HelenaFerreira, Marta Susana20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/86714eng0361-092610.1080/03610926.2022.2050405https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2050405info: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:RCAAP2023-10-14T01:22:26Zoai:repositorium.sdum.uminho.pt:1822/86714Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:35:31.186852Repositório 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 |
A new blocks estimator for the extremal index |
title |
A new blocks estimator for the extremal index |
spellingShingle |
A new blocks estimator for the extremal index Ferreira, Helena Extreme value theory Stationary sequences Dependence conditions Extremal index tail dependence Primary Secondary Primary: 60G70 Secondary: 62G32 Ciências Naturais::Matemáticas Science & Technology Água potável e saneamento |
title_short |
A new blocks estimator for the extremal index |
title_full |
A new blocks estimator for the extremal index |
title_fullStr |
A new blocks estimator for the extremal index |
title_full_unstemmed |
A new blocks estimator for the extremal index |
title_sort |
A new blocks estimator for the extremal index |
author |
Ferreira, Helena |
author_facet |
Ferreira, Helena Ferreira, Marta Susana |
author_role |
author |
author2 |
Ferreira, Marta Susana |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Ferreira, Helena Ferreira, Marta Susana |
dc.subject.por.fl_str_mv |
Extreme value theory Stationary sequences Dependence conditions Extremal index tail dependence Primary Secondary Primary: 60G70 Secondary: 62G32 Ciências Naturais::Matemáticas Science & Technology Água potável e saneamento |
topic |
Extreme value theory Stationary sequences Dependence conditions Extremal index tail dependence Primary Secondary Primary: 60G70 Secondary: 62G32 Ciências Naturais::Matemáticas Science & Technology Água potável e saneamento |
description |
The occurrence of successive extreme observations can have an impact on society. In extreme value theory there are parameters to evaluate the effect of clustering of high values, such as the extremal index. The estimation of the extremal index is a recurrent theme in the literature and there are several methodologies for this purpose. The majority of existing methods depend on two parameters whose choice affects the performance of the estimators. Here we consider a new estimator depending only on one of the parameters, thus contributing to a decrease in the degree of uncertainty. A simulation study presents motivating results. An application to financial data will also be presented. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/86714 |
url |
https://hdl.handle.net/1822/86714 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0361-0926 10.1080/03610926.2022.2050405 https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2050405 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Taylor & Francis |
publisher.none.fl_str_mv |
Taylor & Francis |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799133618289770496 |