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Exponential Ratio Type Estimators of Population Mean under Non-Response

机译:无响应下总体均值的指数比类型估计

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This paper proposes some exponential ratio type estimators of population mean under the situations when certain observations for some sampling units are missing. These missing observations may be for either auxiliary variable or study variable. The biases and mean square errors of the proposed estimators have been derived, up to the first order of approximation. The proposed estimators are compared theoretically with that of the existing ratio type estimators defined by [1]. It has been found that the proposed exponential ratio type estimators perform better than the mean per unit estimator even for the low positive correlation between study variable and auxiliary variable. Moreover, we obtained the conditions for which our proposed estimators are better than the corresponding ratio type estimators of [1]. To verify the theoretical results obtained, a simulation study is carried out finally.
机译:提出了在缺少某些采样单位观测值的情况下,总体均值的指数比类型估计。这些缺失的观察结果可能是针对辅助变量,也可能是研究变量。推导了拟议估计量的偏差和均方误差,直至近似一阶。理论上将建议的估计量与[1]定义的现有比率类型估计量进行比较。已经发现,即使研究变量和辅助变量之间的正相关性较低,所提出的指数比率类型估计器的性能也要优于平均每单位估计器。此外,我们获得了我们提出的估计量优于[1]的相应比率类型估计量的条件。为了验证所获得的理论结果,最后进行了仿真研究。

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