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A Bayesian interpretation of inconsistency measures in cosmology · Around

2019

A Bayesian interpretation of inconsistency measures in cosmology

Lin, Weikang, Ishak, Mustapha

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Measures of discordance between datasets have become an essential part of cosmological analyses.

It is important to accurately evaluate the significance of such discordances when present.
We propose here a Bayesian interpretation of inconsistency measures that can extract information about physical inconsistencies in the presence of data scatter.
The new framework is based on the conditional probability distribution of the level of physical inconsistency given the obtained value of the measure.

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