Assessing Dependences within Multivariate Time Series Partializing the Knowledge of Thirds

A method to estimate from multivariate measurements the dependences within a network of coupled dynamical systems is proposed. The method is non-parametric and resorts to a statistics of the eigen-spectrums of the time series partial correlation matrices. The method is successfully validated on numerically generated data, demonstrating its capability to distinguish between direct and indirect dependences.