• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.使用广义随机化回答模型提高有限总体方差:一种模拟方法。
PLoS One. 2024 Dec 20;19(12):e0315658. doi: 10.1371/journal.pone.0315658. eCollection 2024.
2
Use of an efficient unbiased estimator for finite population mean.使用有效无偏估计量估计有限总体均值。
PLoS One. 2022 Jul 1;17(7):e0270277. doi: 10.1371/journal.pone.0270277. eCollection 2022.
3
A class of ratio estimators of a finite population mean using two auxiliary variables.一类使用两个辅助变量的有限总体均值的比率估计量。
PLoS One. 2014 Feb 24;9(2):e89538. doi: 10.1371/journal.pone.0089538. eCollection 2014.
4
New generalized class of estimators for estimation of finite population mean based on probability proportional to size sampling using two auxiliary variables: A simulation study.基于使用两个辅助变量的与规模成比例概率抽样估计有限总体均值的新广义估计量类:一项模拟研究。
Sci Prog. 2023 Oct-Dec;106(4):368504231208537. doi: 10.1177/00368504231208537.
5
A new approach for estimating variance of a population employing information obtained from a stratified random sampling.一种利用分层随机抽样获得的信息来估计总体方差的新方法。
Heliyon. 2023 Nov 2;9(11):e21477. doi: 10.1016/j.heliyon.2023.e21477. eCollection 2023 Nov.
6
A generalized exponential-type estimator for population mean using auxiliary attributes.利用辅助属性对总体均值进行广义指数型估计。
PLoS One. 2021 May 13;16(5):e0246947. doi: 10.1371/journal.pone.0246947. eCollection 2021.
7
A new improved generalized class of estimators for population distribution function using auxiliary variable under simple random sampling.简单随机抽样下利用辅助变量的总体分布函数的一类新的改进的广义估计量。
Sci Rep. 2023 Apr 3;13(1):5415. doi: 10.1038/s41598-023-30150-9.
8
Construction of improved comprehensive classes of estimators for population distribution function.构建改进的总体分布函数综合类估计量。
Sci Rep. 2024 Sep 9;14(1):20919. doi: 10.1038/s41598-024-70434-2.
9
Modified estimators of finite population distribution function based on dual use of auxiliary information under stratified random sampling.基于分层随机抽样中辅助信息双重利用的有限总体分布函数修正估计量。
Sci Prog. 2022 Jul-Sep;105(3):368504221128486. doi: 10.1177/00368504221128486.
10
A generalized class of estimators for sensitive variable in the presence of measurement error and non-response.存在测量误差和无应答时敏感变量的广义估计器类。
PLoS One. 2022 Jan 19;17(1):e0261561. doi: 10.1371/journal.pone.0261561. eCollection 2022.

本文引用的文献

1
A novel randomized scrambling technique for mean estimation of a finite population.一种用于有限总体均值估计的新型随机置乱技术。
Heliyon. 2024 May 21;10(11):e31690. doi: 10.1016/j.heliyon.2024.e31690. eCollection 2024 Jun 15.
2
An efficient estimator of population variance of a sensitive variable with a new randomized response technique.一种采用新型随机化回答技术的敏感变量总体方差的有效估计量。
Heliyon. 2024 Mar 6;10(5):e27488. doi: 10.1016/j.heliyon.2024.e27488. eCollection 2024 Mar 15.
3
Identifying the generator matrix of a stationary Markov chain using partially observable data.
Chaos. 2024 Feb 1;34(2). doi: 10.1063/5.0156458.
4
An enhanced estimator of finite population variance using two auxiliary variables under simple random sampling.简单随机抽样下使用两个辅助变量的有限总体方差的增强估计量。
Sci Rep. 2023 Dec 5;13(1):21444. doi: 10.1038/s41598-023-44169-5.
5
Efficient estimation of population variance of a sensitive variable using a new scrambling response model.使用一种新的加扰响应模型有效估计敏感变量的总体方差。
Sci Rep. 2023 Nov 14;13(1):19913. doi: 10.1038/s41598-023-45427-2.
6
Randomized response: a survey technique for eliminating evasive answer bias.随机化回答:一种消除回避性回答偏差的调查技术。
J Am Stat Assoc. 1965 Mar;60(309):63-6.

使用广义随机化回答模型提高有限总体方差:一种模拟方法。

Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.

作者信息

Shabbir Javid, Movaheedi Zabihullah

机构信息

Department of Statistics, University of Wah, Wah Cantt, Islamabad, Pakistan.

Faculty of Science, Department of Mathematics, Herat University, Herat, Afghanistan.

出版信息

PLoS One. 2024 Dec 20;19(12):e0315658. doi: 10.1371/journal.pone.0315658. eCollection 2024.

DOI:10.1371/journal.pone.0315658
PMID:39705274
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11661645/
Abstract

Gupta et al. suggested an improved estimator by using the Diana and Perri model in estimating the finite population variance using the single auxiliary variable. On the same lines, Saleem et al. proposed a new scrambled randomized response model (RRT) based on two auxiliary variables for estimating the finite population variance. Recently Azeem et al. presented a new randomized response model in estimating the finite population variance. It is observed that Bias and MSE of these estimators up to first order of approximation seem to lack sufficient information. In this study, we rectify the bias and MSE expressions of the estimators proposed by Gupta et al., Saleem et al. and Azeem et al. Additionally, we suggest a new generalized class of estimators that is more efficient in comparison to the previously considered estimators. A simulation study is conducted to establish the behavior of the estimators. The suggested estimator performs better than the estimators considered by the authors earlier.

摘要

古普塔等人建议在使用单个辅助变量估计有限总体方差时,通过使用戴安娜和佩里模型来改进估计量。同样,萨利姆等人基于两个辅助变量提出了一种新的加扰随机响应模型(RRT)来估计有限总体方差。最近,阿齐姆等人提出了一种用于估计有限总体方差的新随机响应模型。据观察,这些估计量在一阶近似下的偏差和均方误差似乎缺乏足够的信息。在本研究中,我们纠正了古普塔等人、萨利姆等人和阿齐姆等人提出的估计量的偏差和均方误差表达式。此外,我们建议了一类新的广义估计量,与之前考虑的估计量相比,它更有效。进行了一项模拟研究以确定这些估计量的性能。所建议的估计量比作者之前考虑的估计量表现更好。