Maximum-Entropy Priors with Derived Parameters in a Specified Distribution

Maximum-Entropy Priors with Derived Parameters in a Specified Distribution

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.

Bibliographic Details
Main Authors: Will Handley, Marius Millea
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Entropy
Subjects:
maximum entropy
Bayesian inference
prior
derived distribution
neutrino hierarchy
Online Access:http://www.mdpi.com/1099-4300/21/3/272

Internet

http://www.mdpi.com/1099-4300/21/3/272

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