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A new efficient class of estimators of finite population mean in simple random sampling

  • Surya K. PalEmail author
  • Housila P. Singh
  • Ramkrishna S. Solanki
Article
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Abstract

The crux of the paper is to develop a very general class of estimators for population mean \( \bar{Y} \) of the study variable \( y \) using information on auxiliary variable \( x \) in simple random sampling. It has been shown that a large number of known and unknown estimators are members of the suggested class of estimators. Expressions of bias and mean squared errors of the proposed class of estimators have been obtained under large sample approximation. Asymptotic optimum estimator (AOE) in the proposed class of estimators has been obtained with its mean squared error formula. An empirical study is carried out to demonstrate the superiority of the members of the proposed class of estimators over existing estimators.

Keywords

Simple random sampling without replacement (SRSWORBias Mean squared error Efficiency 

Mathematical Subject Classification

62D05 

Notes

Acknowledgements

Authors are thankful to the Editor-in-Chief, Jacek Banasiak and both the learned referees for their precious suggestions.

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Copyright information

© African Mathematical Union and Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Surya K. Pal
    • 1
    Email author
  • Housila P. Singh
    • 2
  • Ramkrishna S. Solanki
    • 3
  1. 1.University School of BusinessChandigarh UniversityMohaliIndia
  2. 2.School of Studies in StatisticsVikram UniversityUjjainIndia
  3. 3.Department of Mathematics and StatisticsCollege of AgricultureWaraseoniIndia

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