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Estimation of finite population mean using auxiliary information in systematic sampling

Author

Listed:
  • Surya K. Pal

    (Vikram University)

  • Housila P. Singh

    (Vikram University)

Abstract

In this paper the problem of estimating the population mean $$\bar{Y}$$ Y ¯ of the study variable $$y$$ y using information on auxiliary variable $$x$$ x in systematic sampling has been considered. Taking motivation from Singh et al. (J Sci Res 56:177–182, 2012a; J Reliab Stat Stud 5(1):73–82, 2012b) we have proposed a class of estimators for the population mean $$\bar{Y}$$ Y ¯ . The bias and mean squared error (MSE) of the suggested class of estimators are obtained. Optimum condition is obtained in which the suggested class of estimators has minimum MSE. A numerical study is provided to show that the members of the proposed class of estimators are more efficient than the other existing estimators.

Suggested Citation

  • Surya K. Pal & Housila P. Singh, 2017. "Estimation of finite population mean using auxiliary information in systematic sampling," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1392-1398, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-017-0609-5
    DOI: 10.1007/s13198-017-0609-5
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    References listed on IDEAS

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    1. Sat Gupta & Javid Shabbir, 2008. "On improvement in estimating the population mean in simple random sampling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(5), pages 559-566.
    2. Giancarlo Diana & Marco Giordan & Pier Perri, 2011. "An improved class of estimators for the population mean," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 123-140, June.
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