Name
Title | ||
|---|---|---|
Generalized Bayes minimax estimation of the normal mean matrix with unknown covariance matrix |
Abstract | ||
|---|---|---|
This paper addresses the problem of estimating the normal mean matrix in the case of unknown covariance matrix. This problem is solved by considering generalized Bayesian hierarchical models. The resulting generalized Bayes estimators with respect to an invariant quadratic loss function are shown to be matricial shrinkage equivariant estimators and the conditions for their minimaxity are given. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.jmva.2009.04.009 | J. Multivariate Analysis |
Keywords | Field | DocType |
invariant quadratic loss function,equivariance,matricial shrinkage equivariant estimator,normal mean matrix,generalized bayes estimation,secondary,posterior mean,minimax estimation,quadratic loss,minimaxity,hierarchical model,shrinkage estimator,unknown covariance matrix,generalized bayes estimator,62c20,62f15,primary,62j07,62c10,multivariate linear model,decision theory,generalized bayesian hierarchical model,covariance matrix,bayes estimator,loss function,bayesian hierarchical model | Econometrics,Minimax,Estimation of covariance matrices,Shrinkage estimator,Matrix (mathematics),Covariance matrix,Statistics,Mathematics,Covariance,Bayes' theorem,Estimator | Journal |
Volume | Issue | ISSN |
100 | 10 | Journal of Multivariate Analysis |
Citations | PageRank | References |
4 | 1.22 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hisayuki Tsukuma | 1 | 8 | 4.66 |