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Ratio- and product-based estimators using known coefficient of variation of the auxiliary variable via modified maximum likelihood

机译：比例——使用已知的和产品为基础的估计辅助的变异系数通过修改最大似然变量

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摘要

In this paper, we improve ratio- and product-based estimators for population mean using known coefficient of variation of the auxiliary variable through modified maximum likelihood. The expressions for biases and mean square errors of the proposed estimators have been obtained theoretically. We obtain some conditions under which the proposed estimators have minimum mean square errors than other existing estimators. For the support of the theoretical outcomes, simulations studies have been made under several super-population models. One real life application for the support of the properties of the proposed estimator has also been given. We also study the robustness properties of the proposed estimators. We show that the use of modified maximum likelihood estimates in estimating finite population mean results to robust estimates under non-normality and outliers. Confidence intervals show that the proposed estimator has shorter confidence intervals and more coverage of estimates than those of the existing estimators.
机译：在本文中,我们改进率,基于产品使用已知的估计总体均值辅助的变异系数通过修改最大似然变量。偏差和均方误差的表达式提出的估计从理论上讲。提出的估计有最低的意思吗广场比其他现有的估计错误。理论成果的支持,模拟研究了几下super-population模型。申请的属性的支持提出了估计也。还研究了鲁棒性的属性提出了估计。修改后的最大似然估计估计有限总体均值的结果在non-normality的可靠估计离群值。提出了估计量有较短的信心间隔和更多的报道估计比这些现有的估计。

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