Preprint Article Version 1 This version is not peer-reviewed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.

Journal reference: Entropy 2018, 20, 709
DOI: 10.3390/e20090709

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.

Subject Areas

change-point detection; conditional entropy; ordinal pattern

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