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Measuring extremal clustering in time series

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Resumo: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.
Autores principais:Ferreira, Marta Susana
Assunto:Extremal index Extreme values theory Stationary sequences
Ano:2023
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho

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