Title
A note on maximum likelihood estimation for covariance reducing models
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
ISSN
0167-7152
Recommended Citation
"A note on maximum likelihood estimation for covariance reducing models" (2012). Faculty Bibliography 2010s. 3265.
https://stars.library.ucf.edu/facultybib2010/3265
Comments
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