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	On the best equivariant estimator of covariance matrix of a multivariate normal population
	Zhang, SL ; Sha, QY
	1997
关键词	multivariate normal distribution best equivariant estimator covariance matrix CONDITIONAL INFERENCE
英文摘要	Let X-1,...,X-n be independently and identically distributed normal m-vectors with mean mu and covariance matrix Sigma with mu'Sigma(-1) mu = C-2 where C > 0 is known. The best equivariant estimator of Sigma under loss functions L-1(Sigma,delta) = tr(Sigma(-1)delta - 1 gamma(Sigma(-1)delta-I) and L-2(Sigma,delta) = tr(Sigma(-1)delta) + log det(Sigma(-1)delta) - m is obtained respectively.; Statistics & Probability; SCI(E); EI; 1; ARTICLE; 8; 2021-2034; 26
语种	英语
出处	EI ; SCI
出版者	communications in statistics theory and methods
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/258180]
专题	数学科学学院
推荐引用方式 GB/T 7714	Zhang, SL,Sha, QY. On the best equivariant estimator of covariance matrix of a multivariate normal population. 1997-01-01.

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