具有共同均值的两个正态总体方差之比的检验能力

IF 1.1 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Statistical Computation and Simulation Pub Date : 2023-11-07 DOI:10.1080/00949655.2023.2276306
Pravash Jena, Manas Ranjan Tripathy
{"title":"具有共同均值的两个正态总体方差之比的检验能力","authors":"Pravash Jena, Manas Ranjan Tripathy","doi":"10.1080/00949655.2023.2276306","DOIUrl":null,"url":null,"abstract":"AbstractThis article addresses the problem of hypothesis testing about the powers of the ratio of variances of two normal populations with a common mean. Different test procedures are proposed, such as the likelihood ratio test, the standardized likelihood ratio test, the parametric bootstrap likelihood ratio test, the computational approach test and its modification. Further, several generalized p-value approach test procedures are derived using some of the existing common mean estimators. The performances of all the suggested test methods are compared numerically in terms of their size values and power functions. In light of our simulation findings, we provide a few suggestions for utilizing the proposed test methods. Finally, we analyse real-life data to show the potential application of the proposed model.Keywords: Bootstrap samplescommon meangeneralized p-valueplug-in estimatorsratio of variancespower functionsimulation studysize value2010 AMS Subject Classifications: 62F0362F0562F1065C05 AcknowledgmentsThe authors would like to sincerely thank the two anonymous reviewers, whose constructive and thoughtful comments on the earlier version of the manuscript led to greater improvements in the manuscript's content.Disclosure statementThe authors declare that there are no relevant financial or non-financial competing interests to report for this work.","PeriodicalId":50040,"journal":{"name":"Journal of Statistical Computation and Simulation","volume":"106 13","pages":"0"},"PeriodicalIF":1.1000,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Testing powers of the ratio of variances of two normal populations with a common mean\",\"authors\":\"Pravash Jena, Manas Ranjan Tripathy\",\"doi\":\"10.1080/00949655.2023.2276306\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractThis article addresses the problem of hypothesis testing about the powers of the ratio of variances of two normal populations with a common mean. Different test procedures are proposed, such as the likelihood ratio test, the standardized likelihood ratio test, the parametric bootstrap likelihood ratio test, the computational approach test and its modification. Further, several generalized p-value approach test procedures are derived using some of the existing common mean estimators. The performances of all the suggested test methods are compared numerically in terms of their size values and power functions. In light of our simulation findings, we provide a few suggestions for utilizing the proposed test methods. Finally, we analyse real-life data to show the potential application of the proposed model.Keywords: Bootstrap samplescommon meangeneralized p-valueplug-in estimatorsratio of variancespower functionsimulation studysize value2010 AMS Subject Classifications: 62F0362F0562F1065C05 AcknowledgmentsThe authors would like to sincerely thank the two anonymous reviewers, whose constructive and thoughtful comments on the earlier version of the manuscript led to greater improvements in the manuscript's content.Disclosure statementThe authors declare that there are no relevant financial or non-financial competing interests to report for this work.\",\"PeriodicalId\":50040,\"journal\":{\"name\":\"Journal of Statistical Computation and Simulation\",\"volume\":\"106 13\",\"pages\":\"0\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Computation and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/00949655.2023.2276306\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Computation and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00949655.2023.2276306","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

摘要本文讨论了具有共同均值的两个正态总体方差之比幂的假设检验问题。提出了不同的检验方法,如似然比检验、标准化似然比检验、参数自举似然比检验、计算方法检验及其修正。此外,利用一些现有的通用均值估计器,推导了几种广义p值方法检验程序。从尺寸值和幂函数的角度对所有测试方法的性能进行了数值比较。根据我们的模拟结果,我们提供了一些建议,利用提出的测试方法。最后,我们分析了实际数据,以显示所提出模型的潜在应用。关键词:Bootstrap样本共同均值广义p值插件估计方差比幂函数模拟研究大小值2010 AMS主题分类:62F0362F0562F1065C05致谢作者衷心感谢两位匿名审稿人,他们对早期版本手稿的建设性和周到的意见使手稿的内容得到了更大的改进。作者声明,本研究没有相关的财务或非财务竞争利益。
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
Testing powers of the ratio of variances of two normal populations with a common mean
AbstractThis article addresses the problem of hypothesis testing about the powers of the ratio of variances of two normal populations with a common mean. Different test procedures are proposed, such as the likelihood ratio test, the standardized likelihood ratio test, the parametric bootstrap likelihood ratio test, the computational approach test and its modification. Further, several generalized p-value approach test procedures are derived using some of the existing common mean estimators. The performances of all the suggested test methods are compared numerically in terms of their size values and power functions. In light of our simulation findings, we provide a few suggestions for utilizing the proposed test methods. Finally, we analyse real-life data to show the potential application of the proposed model.Keywords: Bootstrap samplescommon meangeneralized p-valueplug-in estimatorsratio of variancespower functionsimulation studysize value2010 AMS Subject Classifications: 62F0362F0562F1065C05 AcknowledgmentsThe authors would like to sincerely thank the two anonymous reviewers, whose constructive and thoughtful comments on the earlier version of the manuscript led to greater improvements in the manuscript's content.Disclosure statementThe authors declare that there are no relevant financial or non-financial competing interests to report for this work.
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
Journal of Statistical Computation and Simulation
Journal of Statistical Computation and Simulation 数学-计算机:跨学科应用
CiteScore
2.30
自引率
8.30%
发文量
156
审稿时长
4-8 weeks
期刊介绍: Journal of Statistical Computation and Simulation ( JSCS ) publishes significant and original work in areas of statistics which are related to or dependent upon the computer. Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems. JSCS does not consider applications of statistics to other fields, except as illustrations of the use of the original statistics presented. Accepted papers should ideally appeal to a wide audience of statisticians and provoke real applications of theoretical constructions.
期刊最新文献
Multivariate normality tests with two-step monotone missing data: a critical review with emphasis on the different methods of handling missing values Improved Liu-ridge-type estimates for the beta regression model Variable selection and estimation for recurrent event model with covariates subject to measurement error Comparison of approaches for local testing with functional test statistics Depth for samples of sets with applications to testing equality in distribution of two samples of random sets
×
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