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Estimators Shrinking towards Projection Vector for Multivariate Normal Mean Vector under the Norm with a Known Interval

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Author(s)
Hoh Yoo Back
Issued Date
2018
Keyword
James-Stein Type Estimators Sample Mean Projection Matrix
Abstract
Consider the problem of estimating a 􀆎 􀁚􀃎 mean vector 􀄾 (􀆎 􀃠 􀆐 􀀾 􀃐), 􀆐 􀃡 􀂙􀂈􀂕􀂒􀃞􀂤 􀃟 with a projection matrix 􀂤 under the quadratic loss, based on a sample 􀂲􀃎 􀃬 􀂲􀃏 􀃬 􀁺 􀃬 􀂲􀆌 . In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm 􀃧􀃧 􀄾 􀃠 􀂤 􀄾 􀃧􀃧 is constrain, where 􀂤 is an idempotent and symmetric matrix and 􀂙􀂈􀂕􀂒􀃞􀂤􀃟 􀃡 􀆐 . It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.
Publisher
조선대학교 기초과학연구원
Citation
Hoh Yoo Back. (2018). Estimators Shrinking towards Projection Vector for Multivariate Normal Mean Vector under the Norm with a Known Interval, 조선자연과학논문집 | Vol.11, No.3 p.154 ~ p.160
Type
Laboratory article
ISSN
2005-1042
URI
https://oak.chosun.ac.kr/handle/2020.oak/16478
http://www.chosun.ac.kr/user/indexSub.do?codyMenuSeq=24427455&siteId=ricns&dum=dum&boardId=175013&page=1&command=view&boardSeq=276273&categoryId=266507&categoryDepth=00120003
Appears in Collections:
2018 > Vol.11, No.3
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