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Reliability estimation based on ranked set sampling

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  • Emad El-Neweihi
  • Bikas K. Sinha

Abstract

In this paper we consider the problem of estimating the reliability of an exponential component based on a Ranked Set Sample (RSS) of size n. Given the first r observations of that sample, 1≤r≤n, we construct an unbiased estimator for this reliability and we show that these n unbiased estimators are the only ones in a certain class of estimators. The variances of some of these estimators are compared. By viewing the observations of the RSS of size n as the lifetimes of n independent k-out-of-n systems, 1≤k≤n, we are able to utilize known properties of these systems in conjunction with the powerful tools of majorization and Schur functions to derive our results.

Suggested Citation

  • Emad El-Neweihi & Bikas K. Sinha, 2000. "Reliability estimation based on ranked set sampling," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 29(7), pages 1583-1595, January.
  • Handle: RePEc:taf:lstaxx:v:29:y:2000:i:7:p:1583-1595
    DOI: 10.1080/03610920008832566
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    Cited by:

    1. 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.

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