Evaluating Temporal Correlations in Time Series Using Permutation Entropy, Ordinal Probabilities and Machine Learning

Time series analysis comprises a wide repertoire of methods for extracting information from data sets. Despite great advances in time series analysis, identifying and quantifying the strength of nonlinear temporal correlations remain a challenge. We have recently proposed a new method based on train...

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Detalles Bibliográficos
Autores principales: Boaretto, Bruno R. R., Budzinski, Roberto C., Rossi, Kalel L., Prado, Thiago L., Lopes, Sergio R., Masoller, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391825/
https://www.ncbi.nlm.nih.gov/pubmed/34441165
http://dx.doi.org/10.3390/e23081025

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391825/
https://www.ncbi.nlm.nih.gov/pubmed/34441165
http://dx.doi.org/10.3390/e23081025

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