A widely applicable Bayesian information criterion

Volume: 14, Issue: 1, Pages: 867 - 897
Published: Jan 1, 2013
Abstract
A statistical model or a learning machine is called regular if the map taking a parameter to a probability distribution is one-to-one and if its Fisher information matrix is always positive definite. If otherwise, it is called singular. In regular statistical models, the Bayes free energy, which is defined by the minus logarithm of Bayes marginal likelihood, can be asymptotically approximated by the Schwarz Bayes information criterion (BIC),...
Paper Details
Title
A widely applicable Bayesian information criterion
Published Date
Jan 1, 2013
Volume
14
Issue
1
Pages
867 - 897
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