A novel ratio cum product type exponential class of estimators of finite population mean in Adaptive cluster Sampling
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Abstract
In the present paper a ratio cum product type exponential class of estimators has been proposed to estimate the finite population mean of rare type or hard to reach type population. The mean square error and bias expressions of the proposed generalized class have been derived and presented up to the first order of approximation. New estimators have been developed from the proposed class using robust measures. Using simulation study and a real data application, the efficiency of the newly developed estimators from the class that is proposed have been shown. The results show that the new developed estimators are more efficient than the competing estimators presented in this paper.
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