2010/09/28 by Michael Betancourt, Betancourt, M. J.
Computer Science · #Data Analysis #FOS: Physical sciences #Neural Networks and Applications #Statistics and Probability (physics.data-an)
paper · pdf · doi:10.48550/arxiv.1009.5604
openalex publication_date 2010/09/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.