Testing for nonlinearity in time series: the method of surrogate data
Conference proceedings on Interpretation of time series from nonlinear mechanical systems
Estimation of entropy and mutual information
Neural Computation
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
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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', 'Geweke-Meese-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.