Ranked Set Sampling: A Review with New Initiative on Extreme Ranked Set Sampling

被引：0

作者：

Tiwari, Neeraj ^{[1
]}

Chandra, Girish ^{[2
]}

Nautiyal, Raman ^{[2
]}

机构：

[1] Kumaun Univ, Dept Stat, SSJ Campus, Almora 263601, India

[2] Indian Council Forestry Res & Educ, Div Forestry Stat, Dehra Dun 248006, India

来源：

STATISTICS AND APPLICATIONS | 2019年 / 17卷 / 01期

关键词：

Ranked set sampling; Population ratio; Location and scale parameters; SYMMETRIC DISTRIBUTIONS; AUXILIARY INFORMATION; PARAMETERS; ESTIMATOR; ALLOCATION;

D O I：

暂无

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：

Ranked Set Sampling (RSS) is a sampling scheme, which is mainly used under the condition that the measurement of units are difficult or time consuming but the ranking of the units by some methods other than actual measurements (e.g. visual inspection) is relatively easy. This paper provides a critical review of the major developments and issues in RSS since its inception by McIntyre (1952) and suggests a new initiative on extreme RSS Samawi et al. (1996).

引用

页码：121 / 139

页数：19

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