Maximum-Entropy Priors with Derived Parameters in a Specified Distribution
Statistics Theory
2019-03-13 v3 Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
High Energy Physics - Phenomenology
Statistics Theory
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.
Cite
@article{arxiv.1804.08143,
title = {Maximum-Entropy Priors with Derived Parameters in a Specified Distribution},
author = {Will Handley and Marius Millea},
journal= {arXiv preprint arXiv:1804.08143},
year = {2019}
}
Comments
7 pages, 2 figures, Published in Entropy