| Asymptotically Optimal Empirical Bayes Estimation for Variance Components in Random Effects Models |
| Received:October 14, 2002 |
| Key Words:
Random effects models variance components Bayes estimators empirical Bayes estimators asymptotic optimality.
|
| Fund Project: |
|
| Hits: 2170 |
| Download times: 1185 |
| Abstract: |
| In this paper, the Bayes estimators of variance components for two-way classification random effects models is derived under weighted quadratic loss function, and the empirical Bayes (EB) estimators are constructed by the kernel estimation of multivariate density and its mixed partial derivatives. The asymptotically optimality of the EB estimators are obtained under some suitable conditions, and the special cases and the generalizations of the model are shown. Finally, an example satisfying the conditions of theorem is given. |
| Citation: |
| DOI:10.3770/j.issn:1000-341X.2004.04.010 |
| View Full Text View/Add Comment |
