Two-Phase Ratio Estimation Using Ordinal and Ratio Auxiliary Variables in Non-response

IF 0.8 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Proceedings of the National Academy of Sciences, India Section A: Physical Sciences Pub Date : 2023-06-09 DOI:10.1007/s40010-023-00824-0
R. R. Sinha, Bharti Khanna
{"title":"Two-Phase Ratio Estimation Using Ordinal and Ratio Auxiliary Variables in Non-response","authors":"R. R. Sinha,&nbsp;Bharti Khanna","doi":"10.1007/s40010-023-00824-0","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, problem of estimation of ratio of two population means has been discussed in presence of non-response. A wider two-phase class of estimators has been suggested using ratio and ordinal auxiliary variables under incomplete data due to non-response. Expressions of bias and mean square error of the suggested class of estimators have been derived, and minimum value of mean square error has been obtained under optimum conditions. The properties of the suggested class of estimators have been studied under fixed budget as well as precision. The increase in efficiency of the suggested class of estimators over the relevant estimators has been demonstrated by real data analysis. On the ground of theoretical and empirical studies, it has been explained that suggested class of estimators is efficient than existing conventional estimators.</p></div>","PeriodicalId":744,"journal":{"name":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","volume":"93 4","pages":"695 - 702"},"PeriodicalIF":0.8000,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40010-023-00824-0.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","FirstCategoryId":"103","ListUrlMain":"https://link.springer.com/article/10.1007/s40010-023-00824-0","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper, problem of estimation of ratio of two population means has been discussed in presence of non-response. A wider two-phase class of estimators has been suggested using ratio and ordinal auxiliary variables under incomplete data due to non-response. Expressions of bias and mean square error of the suggested class of estimators have been derived, and minimum value of mean square error has been obtained under optimum conditions. The properties of the suggested class of estimators have been studied under fixed budget as well as precision. The increase in efficiency of the suggested class of estimators over the relevant estimators has been demonstrated by real data analysis. On the ground of theoretical and empirical studies, it has been explained that suggested class of estimators is efficient than existing conventional estimators.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
无响应情况下使用序和比辅助变量的两相比估计
本文讨论了在无响应情况下两总体均值之比的估计问题。在不完全数据无响应的情况下,提出了一种使用比率和序数辅助变量的广义两相估计器。推导了这类估计器的偏置和均方误差的表达式,得到了最优条件下均方误差的最小值。在固定预算和精度条件下,研究了这类估计量的性质。实际数据分析证明了所建议的估计器比相关估计器效率的提高。在理论和实证研究的基础上,说明了这类估计量比现有的常规估计量更有效。
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 去求助
来源期刊
CiteScore
2.60
自引率
0.00%
发文量
37
审稿时长
>12 weeks
期刊介绍: To promote research in all the branches of Science & Technology; and disseminate the knowledge and advancements in Science & Technology
期刊最新文献
Diameter Estimation of \((m,\rho )\)-Quasi Einstein Manifolds IoT Adoption for Smart Cities Waste Management using Pythagorean Fuzzy MEREC-SWARA-ARAS Method Rate of Convergence of \(\lambda\)-Bernstein-Beta type operators Stability Analysis of Hybrid Nanofluid with Inclined MHD and Joule Effects: Flow Reversal and Flow Separation Review on Thermogravimetric Analysis of Carbon Dots
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1