Consistent Testing for Pairwise Dependence in Time Series

Fokianos, K. and Pitsillou, M. (2017) Consistent Testing for Pairwise Dependence in Time Series. Technometrics, 59 (2). pp. 262-270. ISSN 0040-1706

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We consider the problem of testing pairwise dependence for stationary time series. For this, we suggest the use of a Box–Ljung-type test statistic that is formed after calculating the distance covariance function among pairs of observations. The distance covariance function is a suitable measure for detecting dependencies between observations as it is based on the distance between the characteristic function of the joint distribution of the random variables and the product of the marginals. We show that, under the null hypothesis of independence and under mild regularity conditions, the test statistic converges to a normal random variable. The results are complemented by several examples. This article has supplementary material online.

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Journal Article
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Uncontrolled Keywords:
?? distance covarianceempirical characteristic functiongeneralized spectral densitykernelu-statisticv-statisticmodelling and simulationapplied mathematicsstatistics and probability ??
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26 Sep 2018 09:04
Last Modified:
15 Jul 2024 18:22