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The difference-sign runs length distribution in testing for serial independence

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  • Camillo Cammarota

Abstract

We investigate the sequence of difference-sign runs length of a time series in the context of non-parametric tests for serial independence. This sequence is, under suitable conditioning, a stationary sequence and we prove that the normalized correlation of two consecutive runs length is small (≈0.0427). We use this result in a test based on the relative entropy of the empirical distribution of the runs length. We investigate the performance of the test in simulated series and test serial independence of cardiac data series in atrial fibrillation.

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  • Camillo Cammarota, 2011. "The difference-sign runs length distribution in testing for serial independence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 1033-1043, February.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:5:p:1033-1043
    DOI: 10.1080/02664761003758984
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    References listed on IDEAS

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    1. Cammarota, Camillo & Rogora, Enrico, 2005. "Independence and symbolic independence of nonstationary heartbeat series during atrial fibrillation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 323-335.
    2. Urbanowicz, Krzysztof & Żebrowski, Jan J. & Baranowski, Rafał & Hołyst, Janusz A., 2007. "How random is your heart beat?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 439-447.
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    Cited by:

    1. Camillo Cammarota, 2017. "Estimating the turning point location in shifted exponential model of time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(7), pages 1269-1281, May.

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