Correlation Dimension Detects Causal Links in Coupled Dynamical Systems

Anna Krakovská

doi:10.3390/e21090818

journal article Open Access Aug 21, 2019

Correlation Dimension Detects Causal Links in Coupled Dynamical Systems

Anna Krakovská

Entropy Vol. 21 No. 9 pp. 818 · MDPI AG

View at Publisher Save 10.3390/e21090818

Abstract

It is becoming increasingly clear that causal analysis of dynamical systems requires different approaches than, for example, causal analysis of interconnected autoregressive processes. In this study, a correlation dimension estimated in reconstructed state spaces is used to detect causality. If deterministic dynamics plays a dominant role in data then the method based on the correlation dimension can serve as a fast and reliable way to reveal causal relationships between and within the systems. This study demonstrates that the method, unlike most other causal approaches, detects causality well, even for very weak links. It can also identify cases of uncoupled systems that are causally affected by a hidden common driver.

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Details

Published: Aug 21, 2019
Vol/Issue: 21(9)
Pages: 818
License: View

Authors

A

Anna Krakovská

Institute of Measurement Science, Slovak Academy of Sciences, 841 04 Bratislava, Slovakia

Funding

Slovak Grant Agency for Science Award: 2/0081/19

Cite This Article

Anna Krakovská (2019). Correlation Dimension Detects Causal Links in Coupled Dynamical Systems. Entropy, 21(9), 818. https://doi.org/10.3390/e21090818

Correlation Dimension Detects Causal Links in Coupled Dynamical Systems

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