On the Behaviour of Weighted Permutation Entropy on Fractional Brownian Motion in the Univariate and Multivariate Setting

Authors

  • Marisa Mohr Institute of Information Systems, University of Lübeck https://orcid.org/0000-0003-0006-6141
  • Florian Wilhelm
  • Ralf Möller Institute of Information Systems, University of Lübeck

DOI:

https://doi.org/10.32473/flairs.v34i1.128464

Keywords:

fractional Brownian motion, ordinal pattern, time series, stochastic process, feature extraction

Abstract

The estimation of the qualitative behaviour of fractional Brownian motion is an important topic for modelling real-world applications. Permutation entropy is a well-known approach to quantify the complexity of univariate time series in a scalar-valued representation. As an extension often used for outlier detection, weighted permutation entropy takes amplitudes within time series into account. As many real-world problems deal with multivariate time series, these measures need to be extended though. First, we introduce multivariate weighted permutation entropy, which is consistent with standard multivariate extensions of permutation entropy. Second, we investigate the behaviour of weighted permutation entropy on both univariate and multivariate fractional Brownian motion and show revealing results.

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Published

2021-04-18

How to Cite

Mohr, M., Wilhelm, F., & Möller, R. (2021). On the Behaviour of Weighted Permutation Entropy on Fractional Brownian Motion in the Univariate and Multivariate Setting. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128464

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Section

Main Track Proceedings