Bayesian analysis of the covariance matrix of a multivariate normal distribution with a new class of priors
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Publication:2215742
DOI10.1214/19-AOS1891zbMath1471.62280OpenAlexW3049713613MaRDI QIDQ2215742
Chengyuan Song, Dongchu Sun, James O. Berger
Publication date: 14 December 2020
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.aos/1597370677
Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Analysis of variance and covariance (ANOVA) (62J10)
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Posterior propriety of an objective prior for generalized hierarchical normal linear models, An objective prior for hyperparameters in normal hierarchical models, Bayesian estimation of constrained mean-covariance of normal distributions
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Cites Work
- A well-conditioned estimator for large-dimensional covariance matrices
- Covariance estimation: the GLM and regularization perspectives
- Flexible covariance estimation in graphical Gaussian models
- Estimation of a covariance matrix under Stein's loss
- Best equivariant estimators of a Cholesky decomposition
- Estimation of the inverse covariance matrix: Random mixtures of the inverse Wishart matrix and the identity
- The variational form of certain Bayes estimators
- Inference from iterative simulation using multiple sequences
- Estimation of a covariance matrix using the reference prior
- An objective prior for hyperparameters in normal hierarchical models
- Multivariate calculation. Use of the continuous groups
- Statistical paleoclimate reconstructions via Markov random fields
- Posterior propriety and admissibiity of hyperpriors in normal hierarchical models
- Objective priors for the bivariate normal model
- Shrinkage Estimators for Covariance Matrices
- Generation of Random Orthogonal Matrices
- Nonconjugate Bayesian Estimation of Covariance Matrices and Its Use in Hierarchical Models
- A Hierarchical Eigenmodel for Pooled Covariance Estimation
- Monte Carlo sampling methods using Markov chains and their applications
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