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Consistent Testing for Pairwise Dependence in Time Series

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>2017
<mark>Journal</mark>Technometrics
Issue number2
Volume59
Number of pages9
Pages (from-to)262-270
Publication statusPublished
Early online date12/04/17
Original languageEnglish

Abstract

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.