Efficiency of Ratio Estimators under Maximum and Minimum values using Simple Random Sampling Scheme


This paper presents a class of ratio estimators for the estimation of finite population mean under maximum and minimum values and using knowledge of the auxiliary variable. The properties of the proposed estimators in terms of biases and mean square errors are derived up to first order of approximation. Also the performance of the proposed class of estimators are shown theoretically and these theoretically conditions are verified by numerically by taking three natural populations under which the proposed class of estimators performed better than the others competing estimators.

Keywords: Auxiliary variable, Efficiency, Maximum and Minimum values, Mean squared error, Ratio estimators, Simple random sampling, Study variable

Unique Article ID: IJMSS-136

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