NONPARAMETRIC TESTS FOR SERIAL DEPENDENCE

Ngai Hang Chan and Lanh Tat Tran

Journal of Time Series Analysis, 1992, vol. 13, issue 1, 19-28

Abstract: Abstract. A nonparametric test statistic based on the distance between the joint and marginal densities is developed to test for the serial dependence for a given sequence of time series data. The key idea lies in observing that, under the null hypothesis of independence, the joint density of the observations is equal to the product of their individual marginals. Histograms are used in constructing such a statistic which is nonparametric and consistent. It possesses high power in capturing subtle or diffuse dependence structure. A bilinear time series model is used to illustrate its performance with the classical correlation approach.

Date: 1992
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