Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/46971
Título: | Analyzing the Gaver-Lewis Pareto process under an extremal perspective |
Autor(es): | Ferreira, Marta Susana Ferreira, Helena |
Palavras-chave: | Extreme value theory Autoregressive processes Extremal index Asymptotic tail independence |
Data: | 2017 |
Editora: | MDPI |
Revista: | Risks |
Resumo(s): | Pareto processes are suitable to model stationary heavy-tailed data. Here, we consider the auto-regressive Gaver–Lewis Pareto Process and address a study of the tail behavior. We characterize its local and long-range dependence. We will see that consecutive observations are asymptotically tail independent, a feature that is often misevaluated by the most common extremal models and with strong relevance to the tail inference. This also reveals clustering at “penultimate” levels. Linear correlation may not exist in a heavy-tailed context and an alternative diagnostic tool will be presented. The derived properties relate to the auto-regressive parameter of the process and will provide estimators. A comparison of the proposals is conducted through simulation and an application to a real dataset illustrates the procedure. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/46971 |
DOI: | 10.3390/risks5030033 |
ISSN: | 2227-9091 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
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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risks-05-00033-v2 (1).pdf | 591,21 kB | Adobe PDF | Ver/Abrir |