IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Journal of Computational Neuroscience
On directed information theory and Granger causality graphs
Journal of Computational Neuroscience
Causal conditioning and instantaneous coupling in causality graphs
Information Sciences: an International Journal
Hi-index | 754.84 |
New measures are proposed for mutual and causal dependence between two time series, based on information theoretical ideas. The measure of mutual dependence is shown to be the sum of the measure of unidirectional causal dependence from the first time series to the second, the measure of unidirectional causal dependence from the second to the first, and the measure of instantaneous causal dependence. The measures are applicable to any kind of time series: continuous, discrete, or categorical.