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Open AccessArticle

Residual Predictive Information Flow in the Tight Coupling Limit: Analytic Insights from a Minimalistic Model

1
Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, 26129 Oldenburg, Germany
2
ForWind-Center for Wind Energy Research, Institute of Physics, University of Oldenburg, 26129 Oldenburg, Germany
3
Research Center Neurosensory Science, University of Oldenburg, 26129 Oldenburg, Germany
4
Institute of Computer Science of the Czech Academy of Sciences, 18207 Prague, Czech Republic
5
National Institute of Mental Health, 25067 Klecany, Czech Republic
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(10), 1010; https://doi.org/10.3390/e21101010
Received: 30 July 2019 / Revised: 23 September 2019 / Accepted: 11 October 2019 / Published: 17 October 2019
In a coupled system, predictive information flows from the causing to the caused variable. The amount of transferred predictive information can be quantified through the use of transfer entropy or, for Gaussian variables, equivalently via Granger causality. It is natural to expect and has been repeatedly observed that a tight coupling does not permit to reconstruct a causal connection between causing and caused variables. Here, we show that for a model of interacting social groups, carried from the master equation to the Fokker–Planck level, a residual predictive information flow can remain for a pair of uni-directionally coupled variables even in the limit of infinite coupling strength. We trace this phenomenon back to the question of how the synchronizing force and the noise strength scale with the coupling strength. A simplified model description allows us to derive analytic expressions that fully elucidate the interplay between deterministic and stochastic model parts. View Full-Text
Keywords: time series; information transfer; causality time series; information transfer; causality
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Wahl, B.; Feudel, U.; Hlinka, J.; Wächter, M.; Peinke, J.; Freund, J.A. Residual Predictive Information Flow in the Tight Coupling Limit: Analytic Insights from a Minimalistic Model. Entropy 2019, 21, 1010.

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