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Time-Reversibility, Causality and Compression-Complexity
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SYSNO ASEP 0541918 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Time-Reversibility, Causality and Compression-Complexity Author(s) Kathpalia, Aditi (UIVT-O) RID, ORCID, SAI
Nagaraj, N. (IN)Number of authors 2 Article number 327 Source Title Entropy. - : MDPI
Roč. 23, č. 3 (2021)Number of pages 21 s. Language eng - English Country CH - Switzerland Keywords time-reversibility ; time-irreversibility ; temporal asymmetry ; compression-complexity ; effort-to-compress ; compressive potential ; interventional causality ; heart period variability asymmetry ; sunspot numbers Subject RIV BA - General Mathematics OECD category Applied mathematics R&D Projects GA19-16066S GA ČR - Czech Science Foundation (CSF) Method of publishing Open access Institutional support UIVT-O - RVO:67985807 UT WOS 000633595200001 EID SCOPUS 85102958587 DOI 10.3390/e23030327 Annotation Detection of the temporal reversibility of a given process is an interesting time series analysis scheme that enables the useful characterisation of processes and offers an insight into the underlying processes generating the time series. Reversibility detection measures have been widely employed in the study of ecological, epidemiological and physiological time series. Further, the time reversal of given data provides a promising tool for analysis of causality measures as well as studying the causal properties of processes. In this work, the recently proposed Compression-Complexity Causality (CCC) measure (by the authors) is shown to be free of the assumption that the „cause precedes the effect”, making it a promising tool for causal analysis of reversible processes. CCC is a data-driven interventional measure of causality (second rung on the Ladder of Causation) that is based on Effort-to-Compress (ETC), a well-established robust method to characterize the complexity of time series for analysis and classification. For the detection of the temporal reversibility of processes, we propose a novel measure called the Compressive Potential based Asymmetry Measure. This asymmetry measure compares the probability of the occurrence of patterns at different scales between the forward-time and time-reversed process using ETC. We test the performance of the measure on a number of simulated processes and demonstrate its effectiveness in determining the asymmetry of real-world time series of sunspot numbers, digits of the transcedental number π and heart interbeat interval variability. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2022 Electronic address http://dx.doi.org/10.3390/e23030327
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