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Ranked Set Sampling with Non‐Random Selection of Sets and Errors in Ranking

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  • M. S. Ridout
  • J. M. Cobby

Abstract

Ranked set sampling is a technique for estimating the mean of a population, of use when accurate measurement of samples is difficult but ranking sets of samples is relatively easy. In this paper previous work on imperfect ranking is integrated with a simple model of non‐random selection of samples within a set and the effect of these sources of error on the precision of the estimator is examined. The relationship with double sampling is also discussed.

Suggested Citation

  • M. S. Ridout & J. M. Cobby, 1987. "Ranked Set Sampling with Non‐Random Selection of Sets and Errors in Ranking," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(2), pages 145-152, June.
    • Handle: RePEc:bla:jorssc:v:36:y:1987:i:2:p:145-152
    DOI: 10.2307/2347546
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    Cited by:

    1. Kin Lam & Bimal Sinha & Zhong Wu, 1994. "Estimation of parameters in a two-parameter exponential distribution using ranked set sample," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(4), pages 723-736, December.
    2. Gang Zheng & Mohammad Al-Saleh, 2003. "Improving the best linear unbiased estimator for the scale parameter of symmetric distributions by using the absolute value of ranked set samples," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(3), pages 253-265.
    3. Jesse Frey & Omer Ozturk, 2011. "Constrained estimation using judgment post-stratification," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(4), pages 769-789, August.
    4. Vic Barnett & Karen Moore, 1997. "Best linear unbiased estimates in ranked-set sampling with particular reference to imperfect ordering," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(6), pages 697-710.

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