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  Assessing Nonlinear Granger Causality from Multivariate Time Series

Sun, X. (2008). Assessing Nonlinear Granger Causality from Multivariate Time Series. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008) (pp. 440-455). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C72B-B Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C72C-9
Genre: Conference Paper

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 Creators:
Sun, X1, Author           
Daelemans, Editor
W., Editor
Goethals, B., Editor
Morik, K., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: A straightforward nonlinear extension of Granger’s concept of causality in the kernel framework is suggested. The kernel-based approach to assessing nonlinear Granger causality in multivariate time series enables us to determine, in a model-free way, whether the causal relation between two time series is present or not and whether it is direct or mediated by other processes. The trace norm of the so-called covariance operator in feature space is used to measure the prediction error. Relying on this measure, we test the improvement of predictability between time series by subsampling-based multiple testing. The distributional properties of the resulting p-values reveal the direction of Granger causality. Experiments with simulated and real-world data show that our method provides encouraging results.

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 Dates: 2008-09
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: URI: http://www.springerlink.com/content/731x206385873675/fulltext.pdf
DOI: 10.1007/978-3-540-87481-2_29
BibTex Citekey: 5254
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Title: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008)
Place of Event: Antwerpen, Belgium
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Title: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008)
Source Genre: Proceedings
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Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 440 - 455 Identifier: -