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Estimation of the Common Mean of a Bivariate Normal Population

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Abstract

In this paper we discuss the problem of estimating the common mean of a bivariate normal population based on paired data as well as data on one of the marginals. Two double sampling schemes with the second stage sampling being either a simple random sampling (SRS) or a ranked set sampling (RSS) are considered. Two common mean estimators are proposed. It is found that under normality, the proposed RSS common mean estimator is always superior to the proposed SRS common mean estimator and other existing estimators such as the RSS regression estimator proposed by Yu and Lam (1997, Biometrics, 53, 1070–1080). The problem of estimating the mean Reid Vapor Pressure (RVP) of regular gasoline based on field and laboratory data is considered.

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Authors and Affiliations

  1. Department of Statistics and Actuarial Science, The, University of Hong Kong, Pokfulam Road, Hong Kong, CHINA

    Philip L. H. Yu

  2. Department of Mathematics and Statistics, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21228-5398, U.S.A

    Yijun Sun & Bimal K. Sinha

Authors
  1. Philip L. H. Yu
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  2. Yijun Sun
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  3. Bimal K. Sinha
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Yu, P.L.H., Sun, Y. & Sinha, B.K. Estimation of the Common Mean of a Bivariate Normal Population. Annals of the Institute of Statistical Mathematics 54, 861–878 (2002). https://doi.org/10.1023/A:1022475721354

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  • DOI: https://doi.org/10.1023/A:1022475721354

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