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Jackknife empirical likelihood inferences for the population mean with ranked set samples

Author

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  • Zhang, Zhengjia
  • Liu, Tianqing
  • Zhang, Baoxue

Abstract

Without requiring any easily violated assumptions needed by existing rank-based nonparametric methods for ranked set samples, we propose a nonparametric approach for interval estimation and hypothesis testing for the population mean and the difference between two population means with balanced and unbalanced ranked set samples using jackknife empirical likelihood.

Suggested Citation

  • Zhang, Zhengjia & Liu, Tianqing & Zhang, Baoxue, 2016. "Jackknife empirical likelihood inferences for the population mean with ranked set samples," Statistics & Probability Letters, Elsevier, vol. 108(C), pages 16-22.
    • Handle: RePEc:eee:stapro:v:108:y:2016:i:c:p:16-22
    DOI: 10.1016/j.spl.2015.09.016
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    References listed on IDEAS

    as
    1. Jing, Bing-Yi & Yuan, Junqing & Zhou, Wang, 2009. "Jackknife Empirical Likelihood," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1224-1232.
    2. Fligner, Michael A. & MacEachern, Steven N., 2006. "Nonparametric Two-Sample Methods for Ranked-Set Sample Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1107-1118, September.
    3. Ayman Baklizi, 2009. "Empirical likelihood intervals for the population mean and quantiles based on balanced ranked set samples," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 483-505, November.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Yongcheng Qi, 2018. "Jackknife Empirical Likelihood Methods," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(2), pages 20-22, June.

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