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Optimum Stratification in Bivariate Auxiliary Variables under Neyman Allocation

机译:Neyman分配下的二核辅助变量中的最佳分层

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When the complete data set of the study variable is unknown it produces a possible stumbling block in attempting various stratification techniques. A technique is proposed under Neyman allocation when the stratification is done on the two auxiliary variables having one estimation variable under consideration. Because of complexities made by minimal equations, approximate optimum strata boundaries are obtained. An empirical study illustrates the proposed method when the auxiliary variables have standard Cauchy and power distributions.
机译:当研究变量的完整数据集未知时,它在尝试各种分层技术时产生可能的绊脚石。当在考虑的具有一个估计变量的两个辅助变量上进行分层时,在奈曼分配下提出了一种技术。由于最小方程式制造的复杂性,获得了近似最佳的层边界。实证研究说明了当辅助变量具有标准的Cauchy和Power分布时所提出的方法。

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