Almost Unbiased Estimators for Population Coefficient of Variation Using Auxiliary Information

Rajesh Singh, Rohan Mishra, Anamika Kumari, Sunil Kumar Yadav
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Abstract

The objective of the paper is to propose an almost unbiased ratio estimator for the finite coefficient of variation (CV). In this paper, we have proposed an exponential ratio type and log ratio type estimators for estimating population coefficient of variation. Two real data sets and one simulation study is carried out in support of the theoretical results. Mean squared error and Percent relative efficiency criteria is used to assess the performance of the estimators. It has been shown that the proposed class of estimators are almost unbiased up to the first order of approximation. Also proposed estimators are better in efficiency to other estimators consider in this study.
使用辅助信息的人口变异系数近乎无偏估计器
本文的目的是为有限变异系数(CV)提出一种几乎无偏的比率估计器。本文提出了指数比率型和对数比率型估计器,用于估计人口变异系数。为支持理论结果,我们进行了两组真实数据和一项模拟研究。平均平方误差和百分比相对效率标准用于评估估计器的性能。结果表明,所提出的估计器在一阶近似以内几乎是无偏的。此外,与本研究中考虑的其他估计器相比,提议的估计器效率更高。
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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