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Detection of Periodic Autocorrelation in Time Series Data via Zero‐Crossings

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  • Donald E. K. Martin

Abstract

A statistical procedure for detection of periodic autocorrelation in time series data is presented. Intuitively, the probability of a zero‐crossing at time t should be inversely related to the correlation between observations at times t and t− 1. Explicit formulas displaying this inverse relationship are given for mean‐zero periodically correlated time series with certain distributional structures. A test statistic based on this relationship is developed. This testing method provides a robust approach to detection of periodic autocorrelation. Analysis of simulated and actual data sets illustrates the usefulness of the proposed method.

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  • Donald E. K. Martin, 1999. "Detection of Periodic Autocorrelation in Time Series Data via Zero‐Crossings," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(4), pages 435-452, July.
    • Handle: RePEc:bla:jtsera:v:20:y:1999:i:4:p:435-452
    DOI: 10.1111/1467-9892.00148
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