The Annals of Statistics

Invariant normal models with recursive graphical Markov structure

Jesper Madsen

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An extension of the class of GS-LCI normal models introduced by Andersson and Madsen is defined and studied. The models are defined in terms of symmetry restrictions given by a finite group and conditional independence restrictions given by an acyclic directed graph. Maximum likelihood estimation of the parameters in the models is discussed.

Article information

Ann. Statist., Volume 28, Number 4 (2000), 1150-1178.

First available in Project Euclid: 12 March 2002

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62H12: Estimation 62H15: Hypothesis testing
Secondary: 62H10: Distribution of statistics 62H20: Measures of association (correlation, canonical correlation, etc.) 62A05

Group symmetry invariance orthogonal group representation acyclic directed graph conditional independence graphical Markov structure maximum likelihood estimator multivariate normal distribution


Madsen, Jesper. Invariant normal models with recursive graphical Markov structure. Ann. Statist. 28 (2000), no. 4, 1150--1178. doi:10.1214/aos/1015956711.

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