Inadmissibility of non-order-preserving orthogonally invariant estimators of the covariance matrix in the case of Stein's loss
From MaRDI portal
Publication:1186778
DOI10.1016/0047-259X(92)90061-JzbMath0764.62006MaRDI QIDQ1186778
Publication date: 28 June 1992
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
covariance matrixWishart distributionorder-preservinginadmissibilityStein's lossorthogonally invariant estimatororder of sample eigenvalues
Related Items (28)
Estimation of a high-dimensional covariance matrix with the Stein loss ⋮ Orthogonally invariant estimation of the skew-symmetric normal mean matrix ⋮ Estimation of Wishart mean matrices under simple tree ordering ⋮ A regularized profile likelihood approach to covariance matrix estimation ⋮ PREDICTIVE ESTIMATION OF A COVARIANCE MATRIX AND ITS STRUCTURAL PARAMETERS ⋮ Order-preserving Estimators and an Inequality on the Integration of Zonal Polynomial ⋮ On a conjecture of Krishnamoorthy and Gupta ⋮ Estimation of normal covariance matrices parametrized by irreducible symmetric cones under Stein's loss ⋮ The Bayes rule of the parameter in (0,1) under Zhang’s loss function with an application to the beta-binomial model ⋮ Modifying estimators of ordered positive parameters under the Stein loss ⋮ Estimating the covariance matrix: A new approach ⋮ Monotonic minimax estimators of a 2×2 covariance matrix ⋮ A Stein's approach to covariance matrix estimation using regularization of Cholesky factor and log-Cholesky metric ⋮ Robust improvement in estimation of a covariance matrix in an elliptically contoured distribution ⋮ Improving on the sample covariance matrix for a complex elliptically contoured distribution ⋮ Admissibility and minimaxity of Bayes estimators for a normal mean matrix ⋮ Minimax estimators of a covariance matrix ⋮ Asymptotic distribution of Wishart matrix for block-wise dispersion of population eigenvalues ⋮ Estimation of a multivariate normal covariance matrix under a certain structure ⋮ Distribution of eigenvalues and eigenvectors of Wishart matrix when the population eigenvalues are infinitely dispersed and its application to minimax estimation of covariance matrix ⋮ Proper Bayes minimax estimators of the normal mean matrix with common unknown variances ⋮ Other classes of minimax estimators of variance covariance matrix in multivariate normal distribution ⋮ An asymptotic expansion of Wishart distribution when the population eigenvalues are infinitely dispersed ⋮ Inadmissibility of the maximum likelihood estimator of normal covariance matrices with the lattice conditional independence ⋮ Estimating the normal dispersion matrix and the precision matrix from a decision-theoretic point of view: a review ⋮ Improved estimation of the covariance matrix under Stein's loss ⋮ Recent advances in shrinkage-based high-dimensional inference ⋮ Improved nonnegative estimation of multivariate components of variance
Cites Work
This page was built for publication: Inadmissibility of non-order-preserving orthogonally invariant estimators of the covariance matrix in the case of Stein's loss