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Efficiency comparisons for partially rank-ordered set sampling

Author

Listed:
  • Jesse Frey

    () (Villanova University)

  • Timothy G. Feeman

    (Villanova University)

Abstract

Abstract Partially rank-ordered set sampling (PROSS) is a generalization of ranked-set sampling (RSS) in which the ranker is not required to give a full ranking in each set. In this paper, we study the efficiency of the PROSS sample mean under perfect rankings for various PROSS schemes. We obtain conditions under which one PROSS scheme is always more efficient than another, and we also obtain conditions under which how the efficiencies of two PROSS schemes compare depends on the particular distribution. We completely determine how PROSS schemes compare in the two-subset case, and we also prove a conjecture of Ozturk (Environ Ecol Stat 18:757–779, 2011) about how the efficiency of the PROSS sample mean compares to that of the RSS sample mean.

Suggested Citation

  • Jesse Frey & Timothy G. Feeman, 2017. "Efficiency comparisons for partially rank-ordered set sampling," Statistical Papers, Springer, vol. 58(4), pages 1149-1163, December.
  • Handle: RePEc:spr:stpapr:v:58:y:2017:i:4:d:10.1007_s00362-016-0742-2
    DOI: 10.1007/s00362-016-0742-2
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    References listed on IDEAS

    as
    1. A. Hussein & H. Muttlak & E. Al-Sawi, 2013. "Group sequential methods based on ranked set samples," Statistical Papers, Springer, vol. 54(3), pages 547-562, August.
    2. Cem Kadilar & Yesim Unyazici & Hulya Cingi, 2009. "Ratio estimator for the population mean using ranked set sampling," Statistical Papers, Springer, vol. 50(2), pages 301-309, March.
    3. Weiming Li & Tianqing Liu & Zhidong Bai, 2012. "Rounded data analysis based on ranked set sample," Statistical Papers, Springer, vol. 53(2), pages 439-455, May.
    4. Steven N. MacEachern & Ömer Öztürk & Douglas A. Wolfe & Gregory V. Stark, 2002. "A new ranked set sample estimator of variance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 177-188.
    5. Walid Abu-Dayyeh & Esam Al Sawi, 2009. "Modified inference about the mean of the exponential distribution using moving extreme ranked set sampling," Statistical Papers, Springer, vol. 50(2), pages 249-259, March.
    6. Walid Abu-Dayyeh & Aissa Assrhani & Kamarulzaman Ibrahim, 2013. "Estimation of the shape and scale parameters of Pareto distribution using ranked set sampling," Statistical Papers, Springer, vol. 54(1), pages 207-225, February.
    7. Lynne Stokes, 1995. "Parametric ranked set sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 47(3), pages 465-482, September.
    8. Mohammad Jafari Jozani & Saeed Majidi & François Perron, 2012. "Unbiased and almost unbiased ratio estimators of the population mean in ranked set sampling," Statistical Papers, Springer, vol. 53(3), pages 719-737, August.
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