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Measuring causality by taking the directional symbolic mutual information approach
Authors:Chen Gui  Xie Lei  and Chu Jian
Affiliation:Institute of Cyber-System and Control,Zhejiang University,Hangzhou 310027,China
Abstract:We propose a novel measure to assess causality through the comparison of symbolic mutual information between the future of one random quantity and the past of the other.This provides a new perspective that is different from the conventional conceptions.Based on this point of view,a new causality index is derived that uses the definition of directional symbolic mutual information.This measure presents properties that are different from the time delayed mutual information since the symbolization captures the dynamic features of the analyzed time series.In addition to characterizing the direction and the amplitude of the information flow,it can also detect coupling delays.This method has the property of robustness,conceptual simplicity,and fast computational speed.
Keywords:causality measure  Bandt and Pompe method  mutual information  transfer entropy
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