Maximum-Entropy Priors with Derived Parameters in a Specified Distribution

Abstract

We propose a method for transforming probability distributions so that parameters of interest are forced into a specified distribution. We prove that this approach is the maximum entropy choice, and provide a motivating example applicable to neutrino hierarchy inference.

7 pages, 2 figures, Published in Entropy

References in corpus (4)

• Neutrino masses and their ordering: Global Data, Priors and Models
• Cosmic Microwave Background Constraints in Light of Priors Over Reionization Histories
• Objective Bayesian analysis of neutrino masses and hierarchy
• Neutrino Mass Priors for Cosmology from Random Matrices

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