Inferring direct directed-information flow from multivariate nonlinear time series

Michael Jachan, Kathrin Henschel, Jakob Nawrath, Ariane Schad, Jens Timmer, Bjoern Schelter

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Estimating the functional topology of a network from multivariate observations is an important task in nonlinear dynamics. We introduce the nonparametric partial directed coherence that allows disentanglement of direct and indirect connections and their directions. We illustrate the performance of the nonparametric partial directed coherence by means of a simulation with data from synchronized nonlinear oscillators and apply it to real-world data from a patient suffering from essential tremor.

Original languageEnglish
Article number011138
Number of pages5
JournalPhysical Review. E, Statistical, Nonlinear and Soft Matter Physics
Volume80
Issue number1
DOIs
Publication statusPublished - Jul 2009

Cite this

Inferring direct directed-information flow from multivariate nonlinear time series. / Jachan, Michael; Henschel, Kathrin; Nawrath, Jakob; Schad, Ariane; Timmer, Jens; Schelter, Bjoern.

In: Physical Review. E, Statistical, Nonlinear and Soft Matter Physics, Vol. 80, No. 1, 011138, 07.2009.

Research output: Contribution to journalArticle

Jachan, Michael ; Henschel, Kathrin ; Nawrath, Jakob ; Schad, Ariane ; Timmer, Jens ; Schelter, Bjoern. / Inferring direct directed-information flow from multivariate nonlinear time series. In: Physical Review. E, Statistical, Nonlinear and Soft Matter Physics. 2009 ; Vol. 80, No. 1.
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