Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/87022
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Ferreira, Marta Susana | por |
dc.date.accessioned | 2023-10-20T13:41:23Z | - |
dc.date.available | 2023-10-20T13:41:23Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Ferreira, M. (2023, September 20). Smoothness of time series: a new approach to estimation. Communications in Statistics - Simulation and Computation. Informa UK Limited. http://doi.org/10.1080/03610918.2023.2258456 | - |
dc.identifier.issn | 0361-0918 | por |
dc.identifier.uri | https://hdl.handle.net/1822/87022 | - |
dc.description.abstract | The assessment of the risk of occurrence of extreme phenomena is inherently linked to the theory of extreme values. In the context of a time series, the analysis of its trajectory toward a greater or lesser smoothness, i.e. presenting a lesser or greater propensity for oscillations, respectively, constitutes another contribution in the assessment of the risk associated with extreme observations. For example, a financial market index with successive oscillations between high and low values shows investors a more unstable and uncertain behavior. In stationary time series, the upper tail smoothness coefficient is described by the tail dependence coefficient, a well-known concept first introduced by Sibuya. This work focuses on an inferential analysis of the upper tail smoothness coefficient, based on subsampling techniques for time series. In particular, we propose an estimator with reduced bias. We also analyze the estimation of confidence intervals through a block bootstrap methodology and a test procedure to prior detect the presence or absence of smoothness. An application to real data is also presented. | por |
dc.description.sponsorship | The author is very grateful to the reviewers for their comments and suggestions which greatly improved this work. The research of the author as partially financed by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia) within the Projects UIDB/00013/2020 and UIDP/00013/2020. | por |
dc.language.iso | eng | por |
dc.publisher | Taylor & Francis | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00013%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00013%2F2020/PT | por |
dc.rights | openAccess | por |
dc.subject | Block bootstrap | por |
dc.subject | Extreme value theory | por |
dc.subject | Jackknife | por |
dc.subject | Stationary sequences | por |
dc.subject | Tail (in)dependence | por |
dc.title | Smoothness of time series: a new approach to estimation | por |
dc.type | article | - |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.tandfonline.com/doi/full/10.1080/03610918.2023.2258456 | por |
dc.date.updated | 2023-10-17T17:06:51Z | - |
dc.identifier.eissn | 1532-4141 | por |
dc.identifier.doi | 10.1080/03610918.2023.2258456 | por |
dc.subject.fos | Ciências Naturais::Matemáticas | por |
sdum.export.identifier | 12827 | - |
sdum.journal | Communications in Statistics - Simulation and Computation | por |
oaire.version | AM | por |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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FerreiraMsmo_paper_rev_final.pdf | 952,21 kB | Adobe PDF | Ver/Abrir |