Using Rank of the Auxiliary Variable in Estimating Variance of the Stratified Sample Mean

J. Shabbir, Sat Gupta
{"title":"Using Rank of the Auxiliary Variable in Estimating Variance of the Stratified Sample Mean","authors":"J. Shabbir, Sat Gupta","doi":"10.12785/IJCTS/060207","DOIUrl":null,"url":null,"abstract":"We propose a generalized class of estimators for finite population variance using the auxiliary variable as well as rank of the auxiliary variable in stratified sampling. We identify many estimators as special cases of the proposed generalized class of estimators. We discuss the properties of all considered estimators up to first order of approximation. A real data set is used to observe the performances of estimators. It is observed that the proposed generalized class of estimators is more efficient than usual sample variance estimator, traditional ratio estimator, Bahl and Tuteja (1991) exponential ratio type estimator, usual difference estimator and Rao (1991) difference-type estimator.","PeriodicalId":130559,"journal":{"name":"International Journal of Computational & Theoretical Statistics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational & Theoretical Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12785/IJCTS/060207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

We propose a generalized class of estimators for finite population variance using the auxiliary variable as well as rank of the auxiliary variable in stratified sampling. We identify many estimators as special cases of the proposed generalized class of estimators. We discuss the properties of all considered estimators up to first order of approximation. A real data set is used to observe the performances of estimators. It is observed that the proposed generalized class of estimators is more efficient than usual sample variance estimator, traditional ratio estimator, Bahl and Tuteja (1991) exponential ratio type estimator, usual difference estimator and Rao (1991) difference-type estimator.
用辅助变量秩估计分层样本均值方差
在分层抽样中,我们利用辅助变量和辅助变量的秩,提出了有限总体方差的广义估计。我们识别了许多估计量作为所提出的广义类估计量的特殊情况。我们讨论了所有被考虑的估计量直到一阶逼近的性质。用一个真实的数据集来观察估计器的性能。结果表明,所提出的广义类估计量比通常的样本方差估计量、传统的比率估计量、Bahl和Tuteja(1991)指数比率估计量、通常的差分估计量和Rao(1991)差分估计量更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信