A Bayesian Approach To Histogram Comparison
Data Analysis, Statistics and Probability
2010-09-29 v1
Abstract
Determining if two histograms are consistent, whether they have been drawn from the same underlying distribution or not, is a common problem in physics. Existing approaches are not only limited in power but also inapplicable to histograms filled with importance weights, a common feature of Monte Carlo simulations. From a Bayesian perspective, the comparison between a single underlying distribution and two underlying distributions is readily solved within the context of model comparison. I introduce an implementation of Bayesian model comparison to the problem, including the extension to importance sampling.
Cite
@article{arxiv.1009.5604,
title = {A Bayesian Approach To Histogram Comparison},
author = {M. J. Betancourt},
journal= {arXiv preprint arXiv:1009.5604},
year = {2010}
}
Comments
19 pages, 7 figures