分层抽样中新的校正估计量

2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) Pub Date : 2016-12-01 DOI:10.1109/APWC-ON-CSE.2016.022

D. Rao, T. Tekabu, M.G.M. Khan

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引用次数: 6

摘要

校正方法是一种广泛使用的测量抽样方法，它结合了辅助信息来提高测量估计的精度。在本文中，我们提出了两个新的分层抽样总体均值的校准估计，利用已知的辅助信息的平均值和变异系数在每一层。最后给出了一个数值例子来说明所提出的校正估计器的应用和计算细节。此外，还进行了仿真研究，比较了所提出的校正估计器的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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New Calibration Estimators in Stratified Sampling

Calibration approach is widely used survey sampling that incorporates auxiliary information to increase the precision of survey estimates. In this manuscript, we propose two new calibration estimators of population mean in stratified sampling, using the known auxiliary information on mean and coefficient of variation in each stratum. A numerical example is presented to illustrate the application and computational details of the proposed calibration estimators. Moreover, a simulation study is carried out to compare the performance of the proposed calibration estimators.

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2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE)

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