重复测量中估计当前均值的无响应脉冲平差

IF 1.6 Q1 STATISTICS & PROBABILITY Statistica Pub Date : 2018-12-21 DOI:10.6092/ISSN.1973-2201/6930
Priyanka Singh, A. Singh, V. Singh
{"title":"重复测量中估计当前均值的无响应脉冲平差","authors":"Priyanka Singh, A. Singh, V. Singh","doi":"10.6092/ISSN.1973-2201/6930","DOIUrl":null,"url":null,"abstract":"In this paper we have proposed an imputation method based on a family of factor-type estimator to deal with the problem of non-response assuming that the target population has been sampled at two different occasions. The aim is to estimate the current population mean on the basis of matching the sample from the previous occasion and on the basis of fresh sample selected at the current occasion. It has been assumed that the non-response is exhibited by the population at both the occasions and, therefore, the imputation of missing values is required in both the samples, namely, matched sample and fresh sample. Accordingly, a combined point estimator has been suggested after imputation which generates a one-parameter family of estimators. The properties of the estimator have been investigated and the replacement policy has been discussed. Finally, the comparison of the proposed class has been made with another estimator for their performances.","PeriodicalId":45117,"journal":{"name":"Statistica","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2018-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"On the Adjustment of Non-Response through Imputation for Estimating Current Mean in Repeated Surveys\",\"authors\":\"Priyanka Singh, A. Singh, V. Singh\",\"doi\":\"10.6092/ISSN.1973-2201/6930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we have proposed an imputation method based on a family of factor-type estimator to deal with the problem of non-response assuming that the target population has been sampled at two different occasions. The aim is to estimate the current population mean on the basis of matching the sample from the previous occasion and on the basis of fresh sample selected at the current occasion. It has been assumed that the non-response is exhibited by the population at both the occasions and, therefore, the imputation of missing values is required in both the samples, namely, matched sample and fresh sample. Accordingly, a combined point estimator has been suggested after imputation which generates a one-parameter family of estimators. The properties of the estimator have been investigated and the replacement policy has been discussed. Finally, the comparison of the proposed class has been made with another estimator for their performances.\",\"PeriodicalId\":45117,\"journal\":{\"name\":\"Statistica\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2018-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6092/ISSN.1973-2201/6930\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6092/ISSN.1973-2201/6930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 2

摘要

本文提出了一种基于因子型估计量的归算方法,以处理在两个不同场合采样的目标人群的无响应问题。其目的是在匹配前一场合的样本和在当前场合选择的新样本的基础上估计当前总体均值。假设在这两种情况下,总体都表现出不响应,因此,在两个样本中,即匹配样本和新鲜样本中,都需要对缺失值进行imputation。在此基础上,本文提出了一种组合点估计方法,该方法可以生成一组单参数估计量。研究了估计器的性质,并讨论了替换策略。最后,将所提类与另一种估计器的性能进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
On the Adjustment of Non-Response through Imputation for Estimating Current Mean in Repeated Surveys
In this paper we have proposed an imputation method based on a family of factor-type estimator to deal with the problem of non-response assuming that the target population has been sampled at two different occasions. The aim is to estimate the current population mean on the basis of matching the sample from the previous occasion and on the basis of fresh sample selected at the current occasion. It has been assumed that the non-response is exhibited by the population at both the occasions and, therefore, the imputation of missing values is required in both the samples, namely, matched sample and fresh sample. Accordingly, a combined point estimator has been suggested after imputation which generates a one-parameter family of estimators. The properties of the estimator have been investigated and the replacement policy has been discussed. Finally, the comparison of the proposed class has been made with another estimator for their performances.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Statistica
Statistica STATISTICS & PROBABILITY-
CiteScore
1.70
自引率
0.00%
发文量
0
审稿时长
10 weeks
期刊最新文献
A New Discrete Distribution: Properties, Characterizations, Modeling Real Count Data, Bayesian and Non-Bayesian Estimations Polynomial Columns-Parameter Symmetry Model and its Decomposition for Square Contingency Tables A Class of Univariate Non-Mesokurtic Distributions Using a Continuous Uniform Symmetrizer and Chi Generator The Marshall-Olkin Gompertz Distribution: Properties and Applications Estimation of Cumulative Incidence Function in the Presence of Middle Censoring Using Improper Gompertz Distribution
×
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