Estimation of the common mean of a bivariate normal population

Leung Ho Philip YU, Yijun SUN, Bimal K. SINHA

Research output: Contribution to journalArticlespeer-review

8 Citations (Scopus)

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. Copyright © 2002 The Institute of Statistical Mathematics.
Original languageEnglish
Pages (from-to)861-878
JournalAnnals of the Institute of Statistical Mathematics
Volume54
Issue number4
DOIs
Publication statusPublished - 2002

Citation

Yu, P. L. H., Sun, Y., & Sinha, B. K. (2002). Estimation of the common mean of a bivariate normal population. Annals of the Institute of Statistical Mathematics, 54(4), 861-878. doi: 10.1023/A:1022475721354

Keywords

  • Ranked set sampling
  • Relative precision
  • REML
  • Simple random sampling

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