Model selection in the space of Gaussian models invariant by symmetry
Abstract
We consider multivariate centered Gaussian models for the random variable , invariant under the action of a subgroup of the group of permutations on . Using the representation theory of the symmetric group on the field of reals, we derive the distribution of the maximum likelihood estimate of the covariance parameter and also the analytic expression of the normalizing constant of the Diaconis-Ylvisaker conjugate prior for the precision parameter . We can thus perform Bayesian model selection in the class of complete Gaussian models invariant by the action of a subgroup of the symmetric group, which we could also call complete RCOP models. We illustrate our results with a toy example of dimension and several examples for selection within cyclic groups, including a high dimensional example with .
Keywords
Cite
@article{arxiv.2004.03503,
title = {Model selection in the space of Gaussian models invariant by symmetry},
author = {Piotr Graczyk and Hideyuki Ishi and Bartosz Kołodziejek and Hélène Massam},
journal= {arXiv preprint arXiv:2004.03503},
year = {2022}
}
Comments
28 pages of the main text, 15 pages of the Supplementary material, 6 figures, 5 tables. Accepted to Annals of Statistics