Mukherjee, P., Parkinson, D. and Liddle, A. R. (2006) A Nested Sampling Algorithm for Cosmological Model Selection. Astrophysical Journal Letters, 638 (2). L51-L54. ISSN 2041-8205

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Abstract

The abundance of new cosmological data becoming available means that a wider range of cosmological models are testable than ever before. However, an important distinction must be made between parameter fitting and model selection. While parameter fitting simply determines how well a model fits the data, model selection statistics, such as the Bayesian Evidence, are now necessary to choose between these different models, and in particular to assess the need for new parameters. We implement a new evidence algorithm known as nested sampling, which combines accuracy, generality of application and computational feasibility, and apply it to some cosmological datasets and models. We find that a five-parameter model with Harrison–Zel’dovich initial spectrum is currently preferred.

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:	15 Jun 2007
Last Modified:	07 Mar 2017 12:05
URI:	http://srodev.sussex.ac.uk/id/eprint/1125
Google Scholar:	99 Citations

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