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A nonparametric test of stationarity for independent data

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  • Hart, Jeffrey D.

Abstract

A nonparametric test of stationarity for independent data is investigated. The test is based on comparing kernel density estimates calculated from subsamples of the data. Asymptotic distribution theory is developed and results of a modest simulation study are presented.

Suggested Citation

  • Hart, Jeffrey D., 2016. "A nonparametric test of stationarity for independent data," Statistics & Probability Letters, Elsevier, vol. 108(C), pages 40-44.
    • Handle: RePEc:eee:stapro:v:108:y:2016:i:c:p:40-44
    DOI: 10.1016/j.spl.2015.09.024
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    References listed on IDEAS

    as
    1. George Kapetanios, 2007. "Testing for Strict Stationarity," Working Papers 602, Queen Mary University of London, School of Economics and Finance.
    2. George Kapetanios, 2007. "Testing for Strict Stationarity," Working Papers 602, Queen Mary University of London, School of Economics and Finance.
    3. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    4. D. Zhan & J. D. Hart, 2014. "Testing equality of a large number of densities," Biometrika, Biometrika Trust, vol. 101(2), pages 449-464.
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