Information Theoretic Derivations for Causality Detection: Application to Human Gait

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.

• Type: Conference
• Year: 2007
• Where: ICANN
• Authors: Gert Van Dijck, Jo Van Vaerenbergh, Marc M. Van Hulle
• Keywords: Causality Criterion, Conditional Relative Entropy, ICANN 2007, Relative Entropy Criterion