Estimating causal dependencies in networks of nonlinear stochastic dynamical systems.

L. Sommerlade*, M. Eichler, M. Jachan, K. Henschel, J. Timmer, B. Schelter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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 languageEnglish
Pages (from-to)1-9
Number of pages9
JournalPhysical Review E
Publication statusPublished - 1 Jan 2009

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