The cosmology community has been increasingly focusing on Bayesian model selection as a tool to discriminate between competing theories to explain a large amount of data about our Universe. In this paper, I summarize the conceptual underpinnings and the algorithmic implementations of Bayesian model comparison. I then discuss two representative applications of Bayesian model comparison to cosmological problems: determining whether the Universe is infinite and selecting the "best" model of inflation. I conclude by offering some reflections about open challenges and interpretational issues. Help and suggestions from the statistics community would be appreciated in further developing the field. © Springer Science+Business Media New York 2013.
Cosmological bayesian model selection: Recent advances and open challenges / Trotta, R.. - 902:(2012), pp. 127-140. (Intervento presentato al convegno 5th Statistical Challenges in Modern Astronomy Symposium, SCMA 2011 tenutosi a University Park, PA, usa nel 2011) [10.1007/978-1-4614-3520-4_11].
Cosmological bayesian model selection: Recent advances and open challenges
Trotta R.
2012-01-01
Abstract
The cosmology community has been increasingly focusing on Bayesian model selection as a tool to discriminate between competing theories to explain a large amount of data about our Universe. In this paper, I summarize the conceptual underpinnings and the algorithmic implementations of Bayesian model comparison. I then discuss two representative applications of Bayesian model comparison to cosmological problems: determining whether the Universe is infinite and selecting the "best" model of inflation. I conclude by offering some reflections about open challenges and interpretational issues. Help and suggestions from the statistics community would be appreciated in further developing the field. © Springer Science+Business Media New York 2013.File | Dimensione | Formato | |
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