Estimation of finite population mean using auxiliary information in systematic sampling

Surya K. Pal () and Housila P. Singh
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Surya K. Pal: Vikram University
Housila P. Singh: Vikram University

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 67, 1392-1398

Abstract: 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.

Keywords: Auxiliary variable; Study variable; Bias; Mean squared error; Efficiency (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s13198-017-0609-5

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