Simple Unequal Allocation Procedure for Ranked Set Sampling with Skew Distributions

Dinesh S. Bhoj, Girish Chandra
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引用次数: 5

Abstract

A practical unbalanced Ranked Set Sampling (RSS) model is proposed to estimate the population mean of positively skewed distributions. The gains in the relative precisions of the population mean based on the proposed model for chosen distributions are uniformly higher than those based on balanced RSS and the t-model proposed in Kaur et al. (1997). The relative precisions of the simple unequal allocation model are, with one exception, better than (s, t)-model which is better than t-model. The relative precision of the proposed model is very close or equal to the optimal Neyman allocation model.
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具有偏斜分布的排序集抽样的简单不等分配过程
提出了一种实用的不平衡秩集抽样(RSS)模型来估计正偏分布的总体均值。基于所提出的用于所选分布的模型的总体平均值的相对精度的增益均匀地高于基于平衡RSS和Kaur等人提出的t-模型的增益。(1997)。除了一个例外,简单的不平等分配模型的相对精度优于(s,t)-模型,后者优于t模型。所提出的模型的相对精度非常接近或等于最优奈曼分配模型。
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来源期刊
CiteScore
0.50
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0.00%
发文量
5
期刊介绍: The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.
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