Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147029 | Journal of Multivariate Analysis | 2010 | 10 Pages |
Abstract
This paper deals with the problem of estimating the mean matrix in an elliptically contoured distribution with unknown scale matrix. The Laplace and inverse Laplace transforms of the density allow us not only to evaluate the risk function with respect to a quadratic loss but also to simplify expressions of Bayes estimators. Consequently, it is shown that generalized Bayes estimators against shrinkage priors dominate the unbiased estimator.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Hisayuki Tsukuma,