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  A Kernel Test of Nonlinear Granger Causality

Sun, X. (2008). A Kernel Test of Nonlinear Granger Causality. In Workshop on Inference and Estimation in Probabilistic Time-Series Models (pp. 79-89). Cambridge, United Kingdom: Isaac Newton Institute for Mathematical Sciences.

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 Creators:
Sun, X1, Author           
Barber, Editor
D., Editor
Cemgil, A. T., Editor
Chiappa, S., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: We present a novel test of nonlinear Granger causality in bivariate time series. The trace norm of conditional covariance operators is used to capture the prediction errors. Based on this measure, a subsampling-based multiple testing procedure tests the prediction improvement of one time series by the other one. The distributional properties of the resulting p-values reveal the direction of Granger causality. Encouraging results of experiments with simulated and real-world data support our approach.

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 Dates: 2008-06
 Publication Status: Issued
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 Identifiers: URI: http://www.newton.ac.uk/programmes/SCH/schw05-papers.pdf
BibTex Citekey: 5252
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Title: Workshop on Inference and Estimation in Probabilistic Time-Series Models
Place of Event: Cambridge, UK
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Title: Workshop on Inference and Estimation in Probabilistic Time-Series Models
Source Genre: Proceedings
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Publ. Info: Cambridge, United Kingdom : Isaac Newton Institute for Mathematical Sciences
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 79 - 89 Identifier: -