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An Improved Ratio Type Predictive Estimator For Estimating Finite Population Mean Using Auxiliary Information

Authors: Sheela Misra1, Badal Kumar*2;

An Improved Ratio Type Predictive Estimator For Estimating Finite Population Mean Using Auxiliary Information

Abstract

In the present article, motivated by Jeelani et al. (2013), we have made an attempt to develop an improved ratio type estimator of population mean using predictive method of estimation by using linear combination of coefficient of skewness and the quartile deviation of auxiliary variable. The mathematical expressions for the bias and mean squared error (MSE) of the proposed estimator up to the first order approximation have been derived. Theoretical efficiency comparison of proposed estimator with the usual ratio estimator, usual product estimator, and Singh et al. (2014) estimators is also made. To amply corroborate the theoretical findings, an empirical study has also been carried out. The suitability of the proposed estimator can be established and appreciated as it has lesser mean squared error, when compared to other widely used estimators.

Keywords

Predictive Approach, Ratio Estimator, Auxiliary Variable, Bias, Mean Squared Error.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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