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Detection of non-linear structure in time series

  • Matilla-García, Mariano
  • Ruiz Marín, Manuel

In this paper we introduce a new method to detect lags in time series by using permutation entropy. The method is applied to several well-known dynamic processes. The good power performance of the new method in detecting memory structure/lags is notable and gives rise to an expectation that it may form a suitable basis for constructive specification searches.

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File URL: http://www.sciencedirect.com/science/article/B6V84-4W3HX2N-1/2/52b7296a96f082001030d66b2f089c57
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Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 105 (2009)
Issue (Month): 1 (October)
Pages: 1-6

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Handle: RePEc:eee:ecolet:v:105:y:2009:i:1:p:1-6
Contact details of provider: Web page: http://www.elsevier.com/locate/ecolet

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  1. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
  2. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, 09.
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