Two Tests for Dependence (of Unknown Form) between Time Series
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AuthorCaballero Pintado, M Victoria; Matilla García, Mariano; Dona Rodríguez, José Miguel; Ruiz Marín, Manuel
Knowledge AreaEstadística e Investigación Operativa; Matemática Aplicada
SponsorsThis research is the result of the activity performed under the program Groups of Excellence of the Region of Murcia, the Fundación Seneca, Science and Technology Agency of the region of Murcia project under grant 19884/GERM/15. All remaining errors are our responsibility.
Realizado en/conUniversidad Politécnica de Cartagena; Universidad de Murcia; Universidad Nacional de Educación a Distancia
Bibliographic CitationCaballero-Pintado MV, Matilla-García M, Rodríguez JM, Ruiz Marín M. Two Tests for Dependence (of Unknown Form) between Time Series. Entropy. 2019; 21(9):878. https://doi.org/10.3390/e21090878
Symbolic correlation integral
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.
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