Article
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Preserved in Portico This version is not peer-reviewed
Change-Point Detection using the Conditional Entropy of Ordinal Patterns
Version 1
: Received: 27 July 2018 / Approved: 27 July 2018 / Online: 27 July 2018 (16:36:05 CEST)
A peer-reviewed article of this Preprint also exists.
Unakafov, A.M.; Keller, K. Change-Point Detection Using the Conditional Entropy of Ordinal Patterns. Entropy 2018, 20, 709. Unakafov, A.M.; Keller, K. Change-Point Detection Using the Conditional Entropy of Ordinal Patterns. Entropy 2018, 20, 709.
Abstract
This paper is devoted to change-point detection using only the ordinal structure of a time series. A statistic based on the conditional entropy of ordinal patterns characterizing the local up and down in a time series is introduced and investigated. The statistic requires only minimal a priori information on given data and shows good performance in numerical experiments.
Keywords
change-point detection; conditional entropy; ordinal pattern
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright: 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.
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