Title

A note on maximum likelihood estimation for covariance reducing models

Authors

Authors

J. R. Schott

Comments

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Abbreviated Journal Title

Stat. Probab. Lett.

Keywords

Eigenanalysis; Wishart distribution; Statistics & Probability

Abstract

Cook and Forzani (2008) proposed covariance reducing models as a method for modeling the differences among k covariance matrices. The model was developed via a property of a conditional distribution for the sample covariance matrices and this conditional distribution was used to obtain maximum likelihood estimators. In this work, we show that the same maximum likelihood estimators can be obtained using the unconditional distribution of the sample covariance matrices along with a condition on the population covariance matrices that holds if and only if the covariance reducing model holds. In addition, it is shown that when k = 2, specialized numerical methods are not needed to compute the maximum likelihood estimators. (C) 2012 Elsevier B.V. All rights reserved.

Journal Title

Statistics & Probability Letters

Volume

82

Issue/Number

9

Publication Date

1-1-2012

Document Type

Article

Language

English

First Page

1629

Last Page

1631

WOS Identifier

WOS:000306775500001

ISSN

0167-7152

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