Information criteria for astrophysical model selection

Liddle, Andrew R (2007) Information criteria for astrophysical model selection. Monthly Notices of the Royal Astronomical Society, 377 (1). L74-L78. ISSN 0035-8711

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Model selection is the problem of distinguishing competing models, perhaps featuring different numbers of parameters. The statistics literature contains two distinct sets of tools, those based on information theory such as the Akaike Information Criterion (AIC), and those on Bayesian inference such as the Bayesian evidence and Bayesian Information Criterion (BIC). The Deviance Information Criterion combines ideas from both heritages; it is readily computed from Monte Carlo posterior samples and, unlike the AIC and BIC, allows for parameter degeneracy. I describe the properties of the information criteria, and as an example compute them from Wilkinson Microwave Anisotropy Probe 3-yr data for several cosmological models. I find that at present the information theory and Bayesian approaches give significantly different conclusions from that data.

Item Type: Article
Schools and Departments: School of Mathematical and Physical Sciences > Physics and Astronomy
Subjects: Q Science > QC Physics
Depositing User: Andrew Liddle
Date Deposited: 06 Feb 2012 20:16
Last Modified: 02 Jul 2019 20:35

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