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

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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Bibliographic Details
Main Authors: Bruno R. R. Boaretto, Roberto C. Budzinski, Kalel L. Rossi, Thiago L. Prado, Sergio R. Lopes, Cristina Masoller
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Entropy
Subjects:
ordinal analysis
symbolic analysis
machine learning
time series analysis
permutation entropy
complexity
Online Access:https://www.mdpi.com/1099-4300/23/8/1025

Internet

https://www.mdpi.com/1099-4300/23/8/1025

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