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On the Statistical Properties of Multiscale Permutation Entropy: Characterization of the Estimator’s Variance

Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique, Énergétique (PRISME), University of Orléans, 45100 Orléans, INSA-CVL, France
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Entropy 2019, 21(5), 450; https://doi.org/10.3390/e21050450
Received: 30 March 2019 / Revised: 20 April 2019 / Accepted: 26 April 2019 / Published: 30 April 2019
(This article belongs to the Special Issue Multiscale Entropy Approaches and Their Applications)
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Abstract

Permutation Entropy (PE) and Multiscale Permutation Entropy (MPE) have been extensively used in the analysis of time series searching for regularities. Although PE has been explored and characterized, there is still a lack of theoretical background regarding MPE. Therefore, we expand the available MPE theory by developing an explicit expression for the estimator’s variance as a function of time scale and ordinal pattern distribution. We derived the MPE Cramér–Rao Lower Bound (CRLB) to test the efficiency of our theoretical result. We also tested our formulation against MPE variance measurements from simulated surrogate signals. We found the MPE variance symmetric around the point of equally probable patterns, showing clear maxima and minima. This implies that the MPE variance is directly linked to the MPE measurement itself, and there is a region where the variance is maximum. This effect arises directly from the pattern distribution, and it is unrelated to the time scale or the signal length. The MPE variance also increases linearly with time scale, except when the MPE measurement is close to its maximum, where the variance presents quadratic growth. The expression approaches the CRLB asymptotically, with fast convergence. The theoretical variance is close to the results from simulations, and appears consistently below the actual measurements. By knowing the MPE variance, it is possible to have a clear precision criterion for statistical comparison in real-life applications. View Full-Text
Keywords: Multiscale Permutation Entropy; ordinal patterns; estimator variance; Cramér–Rao Lower Bound; finite-length signals Multiscale Permutation Entropy; ordinal patterns; estimator variance; Cramér–Rao Lower Bound; finite-length signals
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Dávalos, A.; Jabloun, M.; Ravier, P.; Buttelli, O. On the Statistical Properties of Multiscale Permutation Entropy: Characterization of the Estimator’s Variance. Entropy 2019, 21, 450.

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