On optimal classes of estimators under ranked set sampling

被引：28

作者：

Bhushan, Shashi ^{[1
]}

Kumar, Anoop ^{[1
]}

机构：

[1] Dr Shakuntala Misra Natl Rehabil Univ, Dept Math & Stat, Lucknow, Uttar Pradesh, India

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2022年 / 51卷 / 08期

关键词：

Ranked set sampling; bias; mean square error; efficiency; LINEAR-REGRESSION; RATIO;

D O I：

10.1080/03610926.2020.1777431

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper proposes some optimal classes of estimators under ranked set sampling. We have acquainted some modifications of the difference and ratio type estimators under ranked set sampling, considered by various authors like Hansen et al., Srivastava, and Walsh in simple random sampling. We have demonstrated that the efficiency of the proposed optimal classes of estimators are always better than the other existing estimators. The theoretical results have been supported by a simulation study carried out over an artificially generated population.

引用

页码：2610 / 2639

页数：30

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