Information Theoretic Derivations for Causality Detection: Application to Human Gait
نویسندگان
چکیده
As a causality criterion we propose the conditional relative entropy. The relationship with information theoretic functionals mutual information and entropy is established. The conditional relative entropy criterion is compared with 3 well-established techniques for causality detection: ‘Sims’, ‘GewekeMeese-Dent’ and ‘Granger’. It is shown that the conditional relative entropy, as opposed to these 3 criteria, is sensitive to0. non-linear causal relationships. All results are illustrated on real-world time series of human gait.
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