Estimation of order-restricted means from correlated data
Journal Article (Journal Article)
In many applications, researchers are interested in estimating the mean of a multivariate normal random vector whose components are subject to order restrictions. Various authors have demonstrated that the likelihood-based methodology may perform poorly under certain conditions for such problems. The problem is much harder when the underlying covariance matrix is nondiagonal. In this paper a simple iterative algorithm is introduced that can be used for estimating the mean of a multivariate normal population when the components are subject to any order restriction. The proposed methodology is illustrated through an application to human reproductive hormone data. © 2005 Biometrika Trust.
Full Text
Duke Authors
Cited Authors
- Peddada, SD; Dunson, DB; Tan, X
Published Date
- September 1, 2005
Published In
Volume / Issue
- 92 / 3
Start / End Page
- 703 - 715
International Standard Serial Number (ISSN)
- 0006-3444
Digital Object Identifier (DOI)
- 10.1093/biomet/92.3.703
Citation Source
- Scopus