We investigate the state space reconstruction from multiple time series derived from continuous and discrete systems and propose a method for building embedding vectors progressively using information measure criteria regarding past, current, and future states. The embedding scheme can be adapted for different purposes, such as mixed modeling, cross-prediction and Granger causality. In particular, we apply this method in order to detect and evaluate information transfer in coupled systems. As a practical application, we investigate in records of scalp epileptic EEG the information flow across brain areas.
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Vlachos et al. (2010) studied this question.
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