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Optimal ranked set sampling estimation based on medians from multiple set sizes

Author

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  • Nader Gemayel
  • Elizabeth Stasny
  • Douglas Wolfe

Abstract

Ranked set sampling (RSS) is a sample selection technique that makes use of expert knowledge to rank sample units before measuring them. Even though rankings are not always perfect, RSS is useful in situations where obtaining measurements is costly, difficult, or destructive. Research in this area has tended to focus on the case where all set sizes are equal. This article represents a departure from that setting because we encounter different set sizes within a single sample. More specifically, we propose an alternative estimator for the median of a symmetric distribution using medians of ranked set samples of various set sizes from such a distribution. This estimator is seen to be robust over a wide class of symmetric distributions.

Suggested Citation

  • Nader Gemayel & Elizabeth Stasny & Douglas Wolfe, 2010. "Optimal ranked set sampling estimation based on medians from multiple set sizes," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 517-527.
    • Handle: RePEc:taf:gnstxx:v:22:y:2010:i:4:p:517-527
    DOI: 10.1080/10485250903301517
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    Cited by:

    1. Nourmohammadi, Mohammad & Jafari Jozani, Mohammad & Johnson, Brad C., 2014. "Confidence intervals for quantiles in finite populations with randomized nomination sampling," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 112-128.
    2. Radhakanta Das & Vivek Verma & Dilip C. Nath, 2017. "Bayesian Estimation Of Measles Vaccination Coverage Under Ranked Set Sampling," Statistics in Transition New Series, Polish Statistical Association, vol. 18(4), pages 589-608, December.
    3. Mohammad Nourmohammadi & Mohammad Jafari Jozani & Brad C. Johnson, 2020. "Parametric Inference Using Nomination Sampling with an Application to Mercury Contamination in Fish," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(1), pages 115-146, February.

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