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Cosmological model selection

2 Pith papers cite this work. Polarity classification is still indexing.

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abstract

Model 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.

fields

astro-ph.CO 2

years

2025 2

verdicts

CONDITIONAL 2

representative citing papers

Beyond CPL: Evidence for dynamical dark energy in three-parameter models

astro-ph.CO · 2025-10-04 · conditional · novelty 4.0

Two three-parameter extensions of the mAH dark energy parametrization are compared to LambdaCDM, wCDM, CPL and others using CMB, DESI BAO, H(z), RSD and three SNIa samples, yielding Delta chi-squared improvements of 6-38 and 2-5 sigma tensions with LambdaCDM.

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