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Open AccessArticle

Two Tests for Dependence (of Unknown Form) between Time Series

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Metodos Cuantitativos para la Economía y la Empresa, Universidad de Murcia, 30100 Murcia, Spain
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Facultad de Económicas y Empresariales, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain
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Departamento Métodos Cuantitativos, Ciencias Juridicas y Lenguas Modernas, Universidad Politecnica de Cartagena, 30201 Cartagena, Spain
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(9), 878; https://doi.org/10.3390/e21090878
Received: 26 July 2019 / Revised: 1 September 2019 / Accepted: 5 September 2019 / Published: 9 September 2019
This paper proposes two new nonparametric tests for independence between time series. Both tests are based on symbolic analysis, specifically on symbolic correlation integral, in order to be robust to potential unknown nonlinearities. The first test is developed for a scenario in which each considered time series is independent and therefore the interest is to ascertain if two internally independent time series share a relationship of an unknown form. This is especially relevant as the test is nuisance parameter free, as proved in the paper. The second proposed statistic tests for independence among variables, allowing these time series to exhibit within-dependence. Monte Carlo experiments are conducted to show the empirical properties of the tests. View Full-Text
Keywords: dependence; permutation entropy; symbolic correlation integral dependence; permutation entropy; symbolic correlation integral
MDPI and ACS Style

Caballero-Pintado, M.V.; Matilla-García, M.; Rodríguez, J.M.; Ruiz Marín, M. Two Tests for Dependence (of Unknown Form) between Time Series. Entropy 2019, 21, 878.

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