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Exponential-Ratio Type Estimators for Population Mean under Ranked Set Sampling

Sarbjit S. Brar, S.C. Malik


In this paper, a class of estimators for estimating the population mean( bar[Y] ) of the study variable(y) has been proposed under ranked set sampling (RSS) using known information of auxiliary variable(x). The expressions for bias and mean square error have been derived for the proposed class of estimators upto first order approximation. An optimum class of estimators of population mean has also been obtained for which mean square error is
minimum. And, it has been proved that the estimators of this optimum class are more efficient than that of existing estimators under RSS. Further, the proposed class of the estimators is more efficient than the class of estimators under simple random sampling (SRS). A simulation study has also been carried out to verify the properties of the proposed class of estimators.


Efficiency, Product Estimator, Ranked Set Sampling, Ratio Estimator, Simple Random Sampling.

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