Bayesian evidence and predictivity of the inflationary paradigm
Giulia Gubitosi, Macarena Lagos, Joao Magueijo, and Rupert Allison

TL;DR
This paper evaluates the scientific status of the inflationary paradigm using Bayesian methods, highlighting the importance of testability and predictivity, and proposing a new measure to assess its falsifiability.
Contribution
It introduces a measure of predictivity and a prior to incorporate falsifiability considerations into Bayesian paradigm evaluation, applied specifically to cosmic inflation.
Findings
Inflation is currently hard to falsify.
Models difficult to falsify are favored by Bayesian evidence.
External data could help falsify inflation in the future.
Abstract
In this paper we consider the issue of paradigm evaluation by applying Bayes' theorem along the following nested hierarchy of progressively more complex structures: i) parameter estimation (within a model), ii) model selection and comparison (within a paradigm), iii) paradigm evaluation. In such a hierarchy the Bayesian evidence works both as the posterior's normalization at a given level and as the likelihood function at the next level up. Whilst raising no objections to the standard application of the procedure at the two lowest levels, we argue that it should receive a considerable modification when evaluating paradigms, when testability and fitting data are equally important. By considering toy models we illustrate how models and paradigms that are difficult to falsify are always favoured by the Bayes factor. We argue that the evidence for a paradigm should not only be high for a…
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