Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/88296
Título: | Measuring extremal clustering in time series |
Autor(es): | Ferreira, Marta Susana |
Palavras-chave: | Extremal index Extreme values theory Stationary sequences |
Data: | 2023 |
Editora: | Multidisciplinary Digital Publishing Institute (MDPI) |
Revista: | Engineering Proceedings |
Resumo(s): | The propensity of data to cluster at extreme values is important for risk assessment. For example, heavy rain over time leads to catastrophic floods. The extremal index is a measure of Extreme Values Theory that allows measurement of the degree of high-value clustering in a time series. Inference about the extremal index requires a prior choice of values for tuning parameters, which impacts the efficiency of existing estimators. In this work, we propose an algorithm that avoids these constraints. Performance is evaluated based on simulations. We also illustrate with real data. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/88296 |
DOI: | 10.3390/engproc2023039064 |
ISSN: | 2673-4591 |
Versão da editora: | https://www.mdpi.com/2673-4591/39/1/64 |
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 | |
---|---|---|---|---|
FerreiraM_rev2.pdf | 687,31 kB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons