Estimating Granger causality from Fourier and wavelet transforms of time series data

Dhamala, Mukeshwar ; Rangarajan, Govindan ; Ding, Mingzhou (2008) Estimating Granger causality from Fourier and wavelet transforms of time series data Physical Review Letters, 100 (1). 018701-018704. ISSN 0031-9007

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Official URL: http://prl.aps.org/abstract/PRL/v100/i1/e018701

Related URL: http://dx.doi.org/10.1103/PhysRevLett.100.018701

Abstract

Experiments in many fields of science and engineering yield data in the form of time series. The Fourier and wavelet transform-based nonparametric methods are used widely to study the spectral characteristics of these time series data. Here, we extend the framework of nonparametric spectral methods to include the estimation of Granger causality spectra for assessing directional influences. We illustrate the utility of the proposed methods using synthetic data from network models consisting of interacting dynamical systems.

Item Type:Article
Source:Copyright of this article belongs to The American Physical Society.
ID Code:73227
Deposited On:02 Dec 2011 09:55
Last Modified:02 Dec 2011 09:55

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