METHODS FOR QUANTIFYING THE CAUSAL STRUCTURE OF BIVARIATE TIME SERIES

DOI10.1142/S0218127407017628zbMath1141.37367OpenAlexW2064549140MaRDI QIDQ3499164

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Publication date: 28 May 2008

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218127407017628

zbMATH Keywords

coupled systemsnonlinear time series analysisinformation flow

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time series analysis of dynamical systems (37M10)

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Cites Work

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• PREDICTABILITY IMPROVEMENT AS AN ASYMMETRICAL MEASURE OF INTERDEPENDENCE IN BIVARIATE TIME SERIES
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• A robust method for detecting interdependences: Application to intracranially recorded EEG

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