Open Access
November 2014 Model comparison with composite likelihood information criteria
Chi Tim Ng, Harry Joe
Bernoulli 20(4): 1738-1764 (November 2014). DOI: 10.3150/13-BEJ539


Comparisons are made for the amount of agreement of the composite likelihood information criteria and their full likelihood counterparts when making decisions among the fits of different models, and some properties of penalty term for composite likelihood information criteria are obtained. Asymptotic theory is given for the case when a simpler model is nested within a bigger model, and the bigger model approaches the simpler model under a sequence of local alternatives. Composite likelihood can more or less frequently choose the bigger model, depending on the direction of local alternatives; in the former case, composite likelihood has more “power” to choose the bigger model. The behaviors of the information criteria are illustrated via theory and simulation examples of the Gaussian linear mixed-effects model.


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Chi Tim Ng. Harry Joe. "Model comparison with composite likelihood information criteria." Bernoulli 20 (4) 1738 - 1764, November 2014.


Published: November 2014
First available in Project Euclid: 19 September 2014

zbMATH: 1357.62086
MathSciNet: MR3263088
Digital Object Identifier: 10.3150/13-BEJ539

Keywords: Akaike information criterion , Bayesian Information Criterion , local alternatives , mixed-effects model , model comparison

Rights: Copyright © 2014 Bernoulli Society for Mathematical Statistics and Probability

Vol.20 • No. 4 • November 2014
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