Restructured class of estimators for population mean using an auxiliary variable under simple random sampling scheme

IF 0.3 Q4 MATHEMATICS, APPLIED Journal of Applied Mathematics Statistics and Informatics Pub Date : 2020-05-01 DOI:10.2478/jamsi-2020-0005
S. Baghel, S. Yadav
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引用次数: 1

Abstract

Abstract The present paper provides a remedy for improved estimation of population mean of a study variable, using the information related to an auxiliary variable in the situations under Simple Random Sampling Scheme. We suggest a new class of estimators of population mean and the Bias and MSE of the class are derived upto the first order of approximation. The least value of the MSE for the suggested class of estimators is also obtained for the optimum value of the characterizing scaler. The MSE has also been compared with the considered existing competing estimators both theoretically and empirically. The theoretical conditions for the increased efficiency of the proposed class, compared to the competing estimators, is verified using a natural population.
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简单随机抽样下使用辅助变量的群体均值的一类重构估计
摘要本文在简单随机抽样方案下,利用辅助变量的相关信息,改进了研究变量总体均值的估计。我们提出了一类新的总体均值估计量,并导出了该类估计量的偏差和均方误差,直至一阶近似。对于表征缩放器的最优值,还获得了所建议的估计类的MSE的最小值。MSE还与所考虑的现有竞争估计器进行了理论和实证比较。与竞争估计器相比,所提出的类的效率提高的理论条件是使用自然总体来验证的。
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来源期刊
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0.00%
发文量
8
审稿时长
20 weeks
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