ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Analyzing multiple nonlinear time series with extended Granger causality

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

[img] PDF
sdarticle.pdf
Restricted to Registered users only

Download (306Kb) | Request a copy

Abstract

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: Journal Article
Additional Information: Copyright of this article belongs to Elsevier.
Keywords: Granger causality;Extended Granger causality;Nonlinear time series;Vector autoregressive models;Delay embedding reconstruction
Department/Centre: Division of Physical & Mathematical Sciences > Centre for Theoretical Studies
Division of Physical & Mathematical Sciences > Mathematics
Date Deposited: 18 Oct 2006
Last Modified: 19 Sep 2010 04:32
URI: http://eprints.iisc.ernet.in/id/eprint/8849

Actions (login required)

View Item View Item