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Improved Family of Ratio Estimators of Finite Population Variance in Stratified Random Sampling

Author

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  • Etebong P C

    (Department of Mathematics and Statistics, University of Uyo, Nigeria)

Abstract

This paper introduces a new family of exponential ratio estimators of population variance in stratified random sampling and studies its properties. Based on Bahl & Tuteja [1], Kadillar & Cingi [2] and Solanki et al. [3], membership of the new family of estimators is identified. Analytical and numerical results show that under certain prescribed conditions, the new estimator has equal optimal efficiency with the regression estimator of population variance but always fares better than the classical ratio estimator of population variance by Isaki [4] and every identified existing estimator of its family.

Suggested Citation

  • Etebong P C, 2018. "Improved Family of Ratio Estimators of Finite Population Variance in Stratified Random Sampling," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(2), pages 48-53, February.
  • Handle: RePEc:adp:jbboaj:v:5:y:2018:i:2:p:48-53
    DOI: 10.19080/BBOAJ.2018.05.555659
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    References listed on IDEAS

    as
    1. Rajesh Tailor & Balkishan Sharma, 2012. "Modified estimators of population variance in presence of auxiliary information," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(1), pages 37-46, March.
    2. Etebong P. Clement & Ekaette I. Enang, 2017. "On the efficiency of ratio estimator over the regression estimator," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(11), pages 5357-5367, June.
    3. Housila Singh & Ramkrishna Solanki, 2013. "A new procedure for variance estimation in simple random sampling using auxiliary information," Statistical Papers, Springer, vol. 54(2), pages 479-497, May.
    Full references (including those not matched with items on IDEAS)

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