双分层抽样框架下总体均值计算的改进策略

IF 0.3 Q4 MATHEMATICS, APPLIED
S. Zeeshan, G. K. Vishwakarma
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引用次数: 0

摘要

本文提出了一种利用两个辅助变量估计有限总体兴趣变量均值的新方法。该技术很好地符合分层总体,其中每个层的比例是通过取一个称为第一阶段样本的初始样本来预测的。当取第一阶段样本时,从第一个样本中取第二个样本,称为第二阶段样本,用于估计兴趣变量的平均值。在我们的研究中,我们考虑了具有两个相关的辅助变量的种群,它们几乎通过了起源。在这种情况下,比值估计技术和乘积估计技术提供了对利益变量均值的改进估计。我们的技术考虑了一种比值积型指数估计量,我们已经从理论上和经验上证明了它的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved strategy for computation of population mean under double stratified sampling framework
Abstract The article contains a new technique to estimate the mean of the variate of the interest of the finite population with the help of two auxiliary variates. The technique complies well with the stratified population in which each strata proportion is predicted by taking an initial sample called the first phase sample. When the first phase sample is taken, a second sample is taken from the first sample which is called the second phase sample which is used to estimate the mean of the variate of the interest. In our study, we have considered the population which has two correlated auxiliary variates that pass almost through the origin. In such a situation ratio estimation technique and product estimation technique that provides improved estimates of the mean of the variate of the interest. Our technique considers a ratio-product type exponential estimator of which we have established efficiency theoretically as well as empirically.
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