Investigating the estimation of the population mean using random ranked set samples

I. Rahimov, H. A. Muttlak*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Ranked set sampling (RSS) uses fixed set size and number of cycles (or replications). In real life however, we may encounter problems that requiring random set size or number of cycles or both. In dealing with such problems we suggest several unbiased estimators of the population mean using random ranked set sampling (RRSS) method in case of perfect ranking and imperfect ranking. The efficiencies of the estimators of the population mean under RRSS and RSS are compared in the case of perfect ranking. The results show, under certain conditions, the efficiency of estimators is improved by using RRSS in the case of perfect ranking. Finally the asymptotic properties of the proposed estimators of the population mean are discussed for prefect and imperfect ranking.

Original languageEnglish
Pages (from-to)311-324
Number of pages14
JournalJournal of Nonparametric Statistics
Volume15
Issue number3
DOIs
StatePublished - Jun 2003

Keywords

  • Asymptotic properties
  • Discrete uniform distribution
  • Efficiency
  • Errors in ranking
  • Random number of replications
  • Random set size
  • Ranked set sampling
  • Relative precision

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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