Copulas and time series with long-ranged dependencies.
Phys Rev E Stat Nonlin Soft Matter Phys
; 89(4): 042117, 2014 Apr.
Article
em En
| MEDLINE
| ID: mdl-24827203
ABSTRACT
We review ideas on temporal dependencies and recurrences in discrete time series from several areas of natural and social sciences. We revisit existing studies and redefine the relevant observables in the language of copulas (joint laws of the ranks). We propose that copulas provide an appropriate mathematical framework to study nonlinear time dependencies and related concepts-like aftershocks, Omori law, recurrences, and waiting times. We also critically argue, using this global approach, that previous phenomenological attempts involving only a long-ranged autocorrelation function lacked complexity in that they were essentially monoscale.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Processamento de Sinais Assistido por Computador
/
Dinâmica não Linear
Tipo de estudo:
Prognostic_studies
/
Qualitative_research
Idioma:
En
Revista:
Phys Rev E Stat Nonlin Soft Matter Phys
Assunto da revista:
BIOFISICA
/
FISIOLOGIA
Ano de publicação:
2014
Tipo de documento:
Article
País de afiliação:
França