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A Generalized Class of Regression-cum-Ratio Estimators of Population Mean in Simple Random Sampling

Manish Kumar, Gajendra K. Vishwakarma


The present paper introduces a general class of regression-cum-ratio estimators for the estimation of population mean of the variable under study. The estimators by Kadilar and Cingi (Applied Mathematics and Computation 151:893-902, 2004), and Kadilar and Cingi (Interstat 4:1-11, 2006) are identified as members of the proposed class of estimators. The expression for mean square error (MSE) of the proposed class has been obtained using Taylor series expansion. The proposed class of estimators has been compared with the other well-known estimators using MSE criterion, and the conditions under which the proposed class performs better have been obtained. Theoretical results have been validated
with the help of an empirical study.


Study variable, Auxiliary variable, Mean square error (MSE), Percent relative efficiency (PRE).

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