This paper is primarily concerned with extending the results of Brandwein and Strawderman in the usual canonical setting of a general linear model when sampling from a spherically symmetric distribution. When the location parameter belongs to a proper linear subspace of the sampling space, we give a
Double Shrinkage Estimators in the GMANOVA Model
โ Scribed by Takeaki Kariya; Yoshihiko Konno; William E. Strawderman
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 333 KB
- Volume
- 56
- Category
- Article
- ISSN
- 0047-259X
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โฆ Synopsis
In the GMANOVA model or equivalent growth curve model, shrinkage effects on the MLE (maximum likelihood estimator) are considered under an invariant risk matrix. We first study the fundamental structure of the problem through which we decompose the estimation problem into some conditional problems and then demonstrate some classes of double shrinkage minimax estimators which uniformly dominate the MLE in the matrix risk.
๐ SIMILAR VOLUMES
The problem of estimating the common regression coefficients is addressed in this paper for two regression equations with possibly different error variances. The feasible generalized least squares (FGLS) estimators have been believed to be admissible within the class of unbiased estimators. It is, n