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On the Ranked-Set Sampling M-Estimates for Symmetric Location Families

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Abstract

The ranked-set sampling (RSS) is applicable in practical problems where the variable of interest for an observed item is costly or time-consuming but the ranking of a set of items according to the variable can be easily done without actual measurement. In this article, the M-estimates of location parameters using RSS data are studied. We deal mainly with symmetric location families. The asymptotic properties of M-estimates based on ranked-set samples are established. The properties of unbalanced ranked-set sample M-estimates are employed to develop the methodology for determining optimal ranked-set sampling schemes. The asymptotic relative efficiencies of ranked-set sample M-estimates are investigated. Some simulation studies are reported.

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Authors and Affiliations

  1. Department of Statistics, University of California, 367 Evans Hall, Berkeley, CA, 94720-3860, U.S.A

    Xiaoyue Zhao

  2. Department of Statistics & Applied Probability, National University of Singapore, 3 Science Drive 2, Singapore, 117543, Republic of Singapore

    Zehua Chen

Authors
  1. Xiaoyue Zhao
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  2. Zehua Chen
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Zhao, X., Chen, Z. On the Ranked-Set Sampling M-Estimates for Symmetric Location Families. Annals of the Institute of Statistical Mathematics 54, 626–640 (2002). https://doi.org/10.1023/A:1022423429880

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  • DOI: https://doi.org/10.1023/A:1022423429880

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