Model selection in cosmology

Liddle, Andrew, Mukherjee, Pia and Parkinson, David (2006) Model selection in cosmology. Astronomy and Geophysics, 47 (4). 4.30-4.33. ISSN 1366-8781

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Model selection aims to determine which theoretical models are most plausible given some data, without necessarily considering preferred values of model parameters. A common model selection question is to ask when new data require introduction of an additional parameter, describing a newly discovered physical effect. We review model selection statistics, then focus on the Bayesian evidence, which implements Bayesian analysis at the level of models rather than parameters. We describe our CosmoNest code, the first computationally efficient implementation of Bayesian model selection in a cosmological context. We apply it to recent WMAP satellite data, examining the need for a perturbation spectral index differing from the scaleinvariant (Harrison–Zel'dovich) case.

Item Type: Article
Schools and Departments: School of Mathematical and Physical Sciences > Physics and Astronomy
Subjects: Q Science > QB Astronomy
Depositing User: SRO Admin
Date Deposited: 28 Feb 2007
Last Modified: 14 Oct 2019 14:15
Google Scholar:27 Citations

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