BAT.jl -- A Julia-based tool for Bayesian inference
Computation
2020-08-10 v1 Instrumentation and Methods for Astrophysics
Machine Learning
High Energy Physics - Experiment
Data Analysis, Statistics and Probability
Abstract
We describe the development of a multi-purpose software for Bayesian statistical inference, BAT.jl, written in the Julia language. The major design considerations and implemented algorithms are summarized here, together with a test suite that ensures the proper functioning of the algorithms. We also give an extended example from the realm of physics that demonstrates the functionalities of BAT.jl.
Cite
@article{arxiv.2008.03132,
title = {BAT.jl -- A Julia-based tool for Bayesian inference},
author = {Oliver Schulz and Frederik Beaujean and Allen Caldwell and Cornelius Grunwald and Vasyl Hafych and Kevin Kröninger and Salvatore La Cagnina and Lars Röhrig and Lolian Shtembari},
journal= {arXiv preprint arXiv:2008.03132},
year = {2020}
}