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Entropy 2016, 18(5), 190; doi:10.3390/e18050190

Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series

Department of Military and Emergency Medicine, Uniformed Services University, Bethesda, MD 20814, USA
Academic Editor: Raúl Alcaraz Martínez
Received: 29 January 2016 / Revised: 4 May 2016 / Accepted: 13 May 2016 / Published: 19 May 2016
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Abstract

We introduce a method for quantifying the inherent unpredictability of a continuous-valued time series via an extension of the differential Shannon entropy rate. Our extension, the specific entropy rate, quantifies the amount of predictive uncertainty associated with a specific state, rather than averaged over all states. We provide a data-driven approach for estimating the specific entropy rate of an observed time series. Finally, we consider three case studies of estimating the specific entropy rate from synthetic and physiological data relevant to the analysis of heart rate variability. View Full-Text
Keywords: information theory; entropy rate; stochastic dynamical system; kernel density estimation information theory; entropy rate; stochastic dynamical system; kernel density estimation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Darmon, D. Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series. Entropy 2016, 18, 190.

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