Estimation of order-restricted means from correlated data

Published

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