Generalized Bayes estimators with closed forms for the normal mean and covariance matrices

DOI10.1016/J.JSPI.2022.06.007OpenAlexW3193627448WikidataQ114154266 ScholiaQ114154266MaRDI QIDQ2676905

Tatsuya Kubokawa, Ryota Yuasa

Publication date: 28 September 2022

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2108.06041

zbMATH Keywords

minimaxitymultivariate normal distributiondominance propertygeneralized BayesEfron-Morris estimator

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On estimation of a matrix of normal means with unknown covariance matrix
• Generalized Bayes minimax estimation of the normal mean matrix with unknown covariance matrix
• Estimation of the mean of a multivariate normal distribution
• Minimax estimation of powers of the variance of a normal population under squared error loss
• Minimax estimators in the normal MANOVA model
• Shrinkage estimation with a matrix loss function
• Shrinkage estimation
• Proper Bayes and minimax predictive densities related to estimation of a normal mean matrix
• Shrinkage estimation for mean and covariance matrices
• A unified approach to estimating a normal mean matrix in high and low dimensions
• A new class of minimax generalized Bayes estimators of a normal variance
• A new class of generalized Bayes minimax ridge regression estimators
• Singular value shrinkage priors for Bayesian prediction
• Estimation under matrix quadratic loss and matrix superharmonicity
• Empirical Bayes on vector observations: An extension of Stein's method

This page was built for publication: Generalized Bayes estimators with closed forms for the normal mean and covariance matrices