Title
A Note On Maximum Likelihood Estimation For Covariance Reducing Models
Keywords
Eigenanalysis; Wishart distribution
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. © 2012 Elsevier B.V.
Publication Date
9-1-2012
Publication Title
Statistics and Probability Letters
Volume
82
Issue
9
Number of Pages
1629-1631
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.spl.2012.05.006
Copyright Status
Unknown
Socpus ID
84861730649 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84861730649
STARS Citation
Schott, James R., "A Note On Maximum Likelihood Estimation For Covariance Reducing Models" (2012). Scopus Export 2010-2014. 4500.
https://stars.library.ucf.edu/scopus2010/4500