Time-Reversibility, Causality and Compression-Complexity

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F21%3A00541918" target="_blank" >RIV/67985807:_____/21:00541918 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.3390/e23030327" target="_blank" >http://dx.doi.org/10.3390/e23030327</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/e23030327" target="_blank" >10.3390/e23030327</a>

Result language

angličtina

Original language name

Time-Reversibility, Causality and Compression-Complexity

Original language description

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.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10102 - Applied mathematics

Project

<a href="/en/project/GA19-16066S" target="_blank" >GA19-16066S: Nonlinear interactions and information transfer in complex systems with extreme events</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Entropy

ISSN

1099-4300

e-ISSN

1099-4300

Volume of the periodical

23

Issue of the periodical within the volume

3

Country of publishing house

CH - SWITZERLAND

Number of pages

21

Pages from-to

327

UT code for WoS article

000633595200001

EID of the result in the Scopus database

2-s2.0-85102958587