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Estimating causal dependencies in networks of nonlinear stochastic dynamical systems
Linda Sommerlade1, Michael Eichler, Michael Jachan
1Department of Physics, University of Freiburg, Hermann-Herder-Str. 3, 79104 Freiburg, Germany. linda.sommerlade@fdm.uni-freiburg.de
Abstract:
The inference of causal interaction structures in multivariate systems enables a deeper understanding of the investigated network. Analyzing nonlinear systems using partial directed coherence requires high model orders of the underlying vector-autoregressive process. We present a method to overcome the drawbacks caused by the high model orders. We calculate the corresponding statistics and provide a significance level. The performance is illustrated by means of model systems and in an application to neurological data.
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