Cosmic Bayes. Datasets and priors in the hunt for dark energy

European Journal for Philosophy of Science 11 (1):1-21 (2021)
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Abstract

Bayesian methods are ubiquitous in contemporary observational cosmology. They enter into three main tasks: cross-checking datasets for consistency; fixing constraints on cosmological parameters; and model selection. This article explores some epistemic limits of using Bayesian methods. The first limit concerns the degree of informativeness of the Bayesian priors and an ensuing methodological tension between task and task. The second limit concerns the choice of wide flat priors and related tension between parameter estimation and model selection. The Dark Energy Survey and its recent Year 1 results illustrate both these limits concerning the use of Bayesianism.

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Michela Massimi
University of Edinburgh

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References found in this work

Theory of Probability.Harold Jeffreys - 1939 - Oxford, England: Clarendon Press.
Theory of Probability.Harold Jeffreys - 1940 - Philosophy of Science 7 (2):263-264.
Philosophy of Cosmology.Chris Smeenk - 2013 - In Robert Batterman (ed.), The Oxford Handbook of Philosophy of Physics. Oxford University Press USA. pp. 607-652.
Can We Justifiably Assume the Cosmological Principle in Order to Break Model Underdetermination in Cosmology?Claus Beisbart - 2009 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 40 (2):175-205.

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