MNRAS-2007-Liddle-L74-8.pdf (456.51 kB)
Information criteria for astrophysical model selection
journal contribution
posted on 2023-06-08, 05:42 authored by Andrew R LiddleModel 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.
History
Publication status
- Published
File Version
- Published version
Journal
Monthly Notices of the Royal Astronomical SocietyISSN
0035-8711Publisher
Wiley-BlackwellExternal DOI
Issue
1Volume
377Page range
L74-L78Department affiliated with
- Physics and Astronomy Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2012-02-06First Open Access (FOA) Date
2016-03-22First Compliant Deposit (FCD) Date
2016-11-10Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC