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The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables

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  • Jingli Lu

Abstract

In sample surveys, it is usual to make use of auxiliary information to increase the precision of the estimators. We propose a new chain ratio estimator and regression estimator of a finite population mean using linear combination of two auxiliary variables and obtain the mean squared error (MSE) equations for the proposed estimators. We find theoretical conditions that make proposed estimators more efficient than the traditional multivariate ratio estimator and the regression estimator using information of two auxiliary variables.

Suggested Citation

  • Jingli Lu, 2013. "The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-4, November.
    • Handle: RePEc:plo:pone00:0081085
    DOI: 10.1371/journal.pone.0081085
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    References listed on IDEAS

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    1. Cem Kadilar & Yesim Unyazici & Hulya Cingi, 2009. "Ratio estimator for the population mean using ranked set sampling," Statistical Papers, Springer, vol. 50(2), pages 301-309, March.
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    Cited by:

    1. Jingli Lu & Zaizai Yan & Xiuyun Peng, 2014. "A New Exponential Ratio-Type Estimator with Linear Combination of Two Auxiliary Variables," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-10, December.
    2. Zulfiqar Ali & Asad Ellahi & Ijaz Hussain & Amna Nazeer & Sadia Qamar & Guangheng Ni & Muhammad Faisal, 2021. "Reduction of Errors in Hydrological Drought Monitoring – A Novel Statistical Framework for Spatio-Temporal Assessment of Drought," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4363-4380, October.

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