Bayesian Inference on Multivariate Normal Covariance and Precision Matrices in a Star-Shaped Model with Missing Data

DOI10.1080/03610920902774251zbMath1188.62174OpenAlexW2144105325MaRDI QIDQ3562437

Zhuoqiong He, Xiaoqian Sun, Dongchu Sun

Publication date: 21 May 2010

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920902774251

zbMATH Keywords

covariance matrixmissing dataentropy lossreference priorJeffreys priorprecision matrixStein losssymmetric lossstar-shaped model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistical aspects of information-theoretic topics (62B10) Basic linear algebra (15A99)

Related Items (1)

The Bayes rule of the parameter in (0,1) under Zhang’s loss function with an application to the beta-binomial model

Cites Work

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• Best equivariant estimators of a Cholesky decomposition
• Empirical Bayes estimation of the multivariate normal covariance matrix
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• Estimation of a covariance matrix using the reference prior
• Estimation of multivariate normal covariance and precision matrices in a star-shape model with missing data
• Estimation of the multivariate normal precision and covariance matrices in a star-shape model
• Maximum Likelihood Estimates for a Multivariate Normal Distribution when some Observations are Missing
• Improved minimax estimation of a normal precision matrix

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