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.
Original language | English |
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Pages (from-to) | 1-9 |
Number of pages | 9 |
Journal | Physical Review E |
Volume | 80 |
DOIs | |
Publication status | Published - 1 Jan 2009 |