Analyzing multiple nonlinear time series with extended Granger causality

Chen, Yonghong ; Rangarajan, Govindan ; Feng, Jianfeng ; Ding, Mingzhou (2004) Analyzing multiple nonlinear time series with extended Granger causality Physics Letters A, 324 (1). pp. 26-35. ISSN 0375-9601

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Identifying causal relations among simultaneously acquired signals is an important problem in multivariate time series analysis. For linear stochastic systems Granger proposed a simple procedure called the Granger causality to detect such relations. In this work we consider nonlinear extensions of Granger's idea and refer to the result as extended Granger causality. A simple approach implementing the extended Granger causality is presented and applied to multiple chaotic time series and other types of nonlinear signals. In addition, for situations with three or more time series we propose a conditional extended Granger causality measure that enables us to determine whether the causal relation between two signals is direct or mediated by another process.

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Granger Causality; Extended Granger Causality; Nonlinear Time Series; Vector Autoregressive Models; Delay Embedding Reconstruction
ID Code:73221
Deposited On:02 Dec 2011 09:51
Last Modified:02 Dec 2011 09:51

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