正则化霍特林 Tn2 的指数边界
IF 1.4 3区 数学 Q2 STATISTICS & PROBABILITY Journal of Multivariate Analysis Pub Date : 2024-06-12 DOI:10.1016/j.jmva.2024.105342
El Mehdi Issouani , Patrice Bertail , Emmanuelle Gautherat

{"title":"正则化霍特林 Tn2 的指数边界</mml:","authors":"El Mehdi Issouani ,&nbsp;Patrice Bertail ,&nbsp;Emmanuelle Gautherat","doi":"10.1016/j.jmva.2024.105342","DOIUrl":null,"url":null,"abstract":"<div><p>We obtain exponential inequalities for regularized Hotelling’s <span><math><msubsup><mrow><mi>T</mi></mrow><mrow><mi>n</mi></mrow><mrow><mn>2</mn></mrow></msubsup></math></span> statistics, that take into account the potential high dimensional aspects of the problem. We explore the finite sample properties of the tail of these statistics by deriving exponential bounds for symmetric distributions and also for general distributions under weak moment assumptions (we never assume exponential moments). For this, we use a penalized estimator of the covariance matrix and propose an optimal choice for the penalty coefficient.</p></div>","PeriodicalId":16431,"journal":{"name":"Journal of Multivariate Analysis","volume":"203 ","pages":"Article 105342"},"PeriodicalIF":1.4000,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0047259X24000496/pdfft?md5=cd918fc00e938bad85311ad3c899e4a8&pid=1-s2.0-S0047259X24000496-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Exponential bounds for regularized Hotelling’s T2 statistic in high dimension\",\"authors\":\"El Mehdi Issouani ,&nbsp;Patrice Bertail ,&nbsp;Emmanuelle Gautherat\",\"doi\":\"10.1016/j.jmva.2024.105342\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We obtain exponential inequalities for regularized Hotelling’s <span><math><msubsup><mrow><mi>T</mi></mrow><mrow><mi>n</mi></mrow><mrow><mn>2</mn></mrow></msubsup></math></span> statistics, that take into account the potential high dimensional aspects of the problem. We explore the finite sample properties of the tail of these statistics by deriving exponential bounds for symmetric distributions and also for general distributions under weak moment assumptions (we never assume exponential moments). For this, we use a penalized estimator of the covariance matrix and propose an optimal choice for the penalty coefficient.</p></div>\",\"PeriodicalId\":16431,\"journal\":{\"name\":\"Journal of Multivariate Analysis\",\"volume\":\"203 \",\"pages\":\"Article 105342\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0047259X24000496/pdfft?md5=cd918fc00e938bad85311ad3c899e4a8&pid=1-s2.0-S0047259X24000496-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Multivariate Analysis\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0047259X24000496\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Multivariate Analysis","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0047259X24000496","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0

摘要

我们获得了正则化霍特林 Tn2 统计量的指数不等式,其中考虑到了问题的潜在高维方面。我们通过推导对称分布以及弱矩假设下一般分布(我们从不假设指数矩)的指数边界,探索了这些统计量尾部的有限样本特性。为此,我们使用了协方差矩阵的惩罚估计器,并提出了惩罚系数的最优选择。
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
Exponential bounds for regularized Hotelling’s T2 statistic in high dimension

We obtain exponential inequalities for regularized Hotelling’s Tn2 statistics, that take into account the potential high dimensional aspects of the problem. We explore the finite sample properties of the tail of these statistics by deriving exponential bounds for symmetric distributions and also for general distributions under weak moment assumptions (we never assume exponential moments). For this, we use a penalized estimator of the covariance matrix and propose an optimal choice for the penalty coefficient.

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 Multivariate Analysis
Journal of Multivariate Analysis 数学-统计学与概率论
CiteScore
2.40
自引率
25.00%
发文量
108
审稿时长
74 days
期刊介绍: Founded in 1971, the Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly innovative applications pertaining to the analysis and interpretation of multidimensional data. The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including cluster analysis, discriminant analysis, factor analysis, and multidimensional continuous or discrete distribution theory. Topics of current interest include, but are not limited to, inferential aspects of Copula modeling Functional data analysis Graphical modeling High-dimensional data analysis Image analysis Multivariate extreme-value theory Sparse modeling Spatial statistics.
期刊最新文献
Sparse functional varying-coefficient mixture regression Maximum likelihood estimation of elliptical tail Covariance parameter estimation of Gaussian processes with approximated functional inputs PDE-regularised spatial quantile regression Diagnostic checking of periodic vector autoregressive time series models with dependent errors
×
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