Causal network reconstruction from time series: From theoretical assumptions to practical estimation

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Ridge Regression: Biased Estimation for Nonorthogonal Problems

Arthur E. Hoerl, Robert Kennard (1970)

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The max-min hill-climbing Bayesian network structure learning algorithm

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We propose to estimate transfer entropy using a technique of symbolization. We demonstrate numerically that symbolic transfer entropy is a robust and computationally fast method to quantify the dominating direction of information flow between time series from structurally identical and nonidentical coupled systems. Analyzing multiday, multichannel electroencephalographic recordings from 15 epilepsy patients our approach allowed us to reliably identify the hemisphere containing the epileptic focus without observing actual seizure activity.

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Author and article information

Journal

Title: Chaos: An Interdisciplinary Journal of Nonlinear Science

Abbreviated Title: Chaos

Publisher: AIP Publishing

ISSN (Print): 1054-1500

ISSN (Electronic): 1089-7682

Publication date Created: July 2018

Publication date (Print): July 2018

Volume: 28

Issue: 7

Page: 075310

Affiliations

[1 ]German Aerospace Center, Institute of Data Science, Jena 07745, Germany

Article

DOI: 10.1063/1.5025050

PubMed ID: 30070533

SO-VID: f664f420-c4b4-42a8-b674-2f5ab4095b4a

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