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Residual predictive information flow in the tight coupling limit: Analytic insights from a minimalistic model
- 1.0511378 - ÚI 2020 RIV CH eng J - Journal Article
Wahl, B. - Feudel, U. - Hlinka, Jaroslav - Wächter, M. - Peinke, J. - Freund, J.A.
Residual predictive information flow in the tight coupling limit: Analytic insights from a minimalistic model.
Entropy. Roč. 21, č. 10 (2019), č. článku 1010. E-ISSN 1099-4300
R&D Projects: GA ČR(CZ) GA19-11753S; GA MZd(CZ) NV17-28427A
Grant - others:GA MŠk(CZ) LO1611
Institutional support: RVO:67985807
Keywords : time series * information transfer * causality
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 2.494, year: 2019
Method of publishing: Open access
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.
Permanent Link: http://hdl.handle.net/11104/0301657
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