Improvement on the Best Invariant Estimators of the Normal Covariance and Precision Matrices via a Lower Triangular Subgroup

Hisayuki Tsukuma
{"title":"Improvement on the Best Invariant Estimators of the Normal Covariance and Precision Matrices via a Lower Triangular Subgroup","authors":"Hisayuki Tsukuma","doi":"10.14490/JJSS.44.195","DOIUrl":null,"url":null,"abstract":"This paper addresses the problems of estimating the normal covariance and precision matrices. A commutator subgroup of lower triangular matrices is considered for deriving a class of invariant estimators. The class shows inadmissibility of the best invariant and minimax estimator of the covariance matrix relative to quadratic loss. Also, in estimation of the precision matrix, a dominance result is given for improvement on a minimax estimator relative to the Stein loss.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Japan Statistical Society. Japanese issue","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14490/JJSS.44.195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

This paper addresses the problems of estimating the normal covariance and precision matrices. A commutator subgroup of lower triangular matrices is considered for deriving a class of invariant estimators. The class shows inadmissibility of the best invariant and minimax estimator of the covariance matrix relative to quadratic loss. Also, in estimation of the precision matrix, a dominance result is given for improvement on a minimax estimator relative to the Stein loss.
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
下三角子群对正态协方差和精度矩阵最优不变估计的改进
本文讨论了正态协方差和精度矩阵的估计问题。考虑了下三角矩阵的交换子群,用于导出一类不变估计量。证明了协方差矩阵的最佳不变估计和极大极小估计对于二次损失的不可容许性。此外,在精度矩阵的估计中,给出了相对于Stein损失的极大极小估计器的优势性改进结果。
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
自引率
0.00%
发文量
0
期刊最新文献
Nonparametric tests for the effect of treatment on conditional variance Purely Sequential and Two-Stage Bounded-Length Confidence Interval Estimation Problems in Fisher’s “Nile” Example Poisson Approximations for Sum of Bernoulli Random Variables and its Application to Ewens Sampling Formula A High-Dimensional Two-Sample Test for Non-Gaussian Data under a Strongly Spiked Eigenvalue Model Approximation of the Meta-Analytic-Predictive Prior Distribution in the One-Way Random Effects Model with Unknown Variance
×
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