An extended class of minimax generalized Bayes estimators of regression coefficients
We derive minimax generalized Bayes estimators of regression coefficients in the general linear model with spherically symmetric errors under invariant quadratic loss for the case of unknown scale. The class of estimators generalizes the class considered in Maruyama and Strawderman [Y. Maruyama, W.E. Strawderman, A new class of generalized Bayes minimax ridge regression estimators, Ann. Statist., 33 (2005) 1753-1770] to include non-monotone shrinkage functions.
Year of publication: |
2009
|
---|---|
Authors: | Maruyama, Yuzo ; Strawderman, William E. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 100.2009, 10, p. 2155-2166
|
Publisher: |
Elsevier |
Keywords: | Regression Minimaxity Shrinkage estimators Generalized Bayes estimators Invariant loss Unknown variance Hypergeometric function |
Saved in:
Saved in favorites
Similar items by person
-
Estimation - Necessary conditions for dominating the James-Stein estimator
Maruyama, Yuzo, (2005)
-
Minimax estimators of a normal variance
Maruyama, Yuzo, (1999)
-
Maruyama, Yuzo, (2003)
- More ...