Graphical Gaussian models with edge and vertex symmetries

Journal article

Abstract:: Summary. We introduce new types of graphical Gaussian models by placing symmetry restrictions on the concentration or correlation matrix. The models can be represented by coloured graphs, where parameters that are associated with edges or vertices of the same colour are restricted to being identical. We study the properties of such models and derive the necessary algorithms for calculating maximum likelihood estimates. We identify conditions for restrictions on the concentration and correlati...
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Role:

Author

Institution:

University of Oxford

Division:

MPLS

Department:

Statistics

Role:

Author

Journal:: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
Volume:: 70
Issue:: 5
Pages:: 1005-1027
Publication date:: 2008-11-01
DOI:: 10.1111/j.1467-9868.2008.00666.x
EISSN:: 1467-9868
ISSN:: 1369-7412

Language:: English
Keywords:: Patterned covariance matrices

Transformation models

Covariance selection

Permutation symmetry

Iterative partial maximization

Invariance

Conditional independence
Pubs id:: pubs:97522
UUID:: uuid:fb41026a-7f7e-4901-a993-09173ea920f4
Local pid:: pubs:97522
Source identifiers:: 97522
Deposit date:: 2012-12-19

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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