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Mean estimate in ranked set sampling using a length-biased concomitant variable

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Listed:
  • Chang Cui
  • Tao Li
  • Lei Zhang

Abstract

In this paper, a ranked set sampling procedure with ranking based on a length-biased concomitant variable is proposed. The estimate for population mean based on this sample is given. It is proved that the estimate based on ranked set samples is asymptotically more efficient than the estimate based on simple random samples. Simulation studies are conducted to present the properties of the proposed estimate for finite sample size. Moreover, the consequence of ignoring length bias is also addressed by simulation studies and the real data analysis.

Suggested Citation

  • Chang Cui & Tao Li & Lei Zhang, 2019. "Mean estimate in ranked set sampling using a length-biased concomitant variable," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(12), pages 2917-2931, June.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:12:p:2917-2931
    DOI: 10.1080/03610926.2018.1473594
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