BAT - The Bayesian Analysis Toolkit
Data Analysis, Statistics and Probability
2015-05-13 v1 Computational Physics
Abstract
We describe the development of a new toolkit for data analysis. The analysis package is based on Bayes' Theorem, and is realized with the use of Markov Chain Monte Carlo. This gives access to the full posterior probability distribution. Parameter estimation, limit setting and uncertainty propagation are implemented in a straightforward manner. A goodness-of-fit criterion is presented which is intuitive and of great practical use.
Keywords
Cite
@article{arxiv.0808.2552,
title = {BAT - The Bayesian Analysis Toolkit},
author = {Allen Caldwell and Daniel Kollar and Kevin Kroeninger},
journal= {arXiv preprint arXiv:0808.2552},
year = {2015}
}
Comments
31 pages, 10 figures