Cosmological model selection

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dc.creatorLiddle, Andrew R.
dc.creatorMukherjee, Pia
dc.creatorParkinson, David
dc.date2006-08-09
dc.date.accessioned2026-07-07T10:39:45Z
dc.date.available2026-07-07T10:39:45Z
dc.descriptionModel selection aims to determine which theoretical models are most plausible given some data, without necessarily asking about the preferred values of the 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 several model selection statistics, and then focus on use of the Bayesian evidence, which implements the usual Bayesian analysis framework at the level of models rather than parameters. We describe our CosmoNest code, which is 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 scale-invariant (Harrison-Zel'dovich) case.
dc.descriptionSemi-technical overview article (10 pages) for RAS house publication A&G. Code at http://cosmonest.org and described in astro-ph/0605003
dc.identifierhttps://arxiv.org/abs/astro-ph/0608184
dc.identifierhttp://arxiv.org/abs/astro-ph/0608184
dc.identifierAstron.Geophys.47:4.30-4.33,2006
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/181138
dc.subjectAstrophysics
dc.titleCosmological model selection
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