https://doi.org/10.1051/epjconf/202024506001
BAT.jl Upgrading the Bayesian Analysis Toolkit
1
Max Planck Institute for Physics, Munich
2
TU Dortmund University, Dortmund
* e-mail: cornelius.grunwald@tu-dortmund.de
Published online: 16 November 2020
In all but the simplest cases, performing data analysis based on Bayesian reasoning requires the use of advanced algorithms. The Bayesian Analysis Toolkit (BAT) provides a collection of algorithms and methods that facilitate the application of Bayesian statistics to user-defined problems of arbitrary complexity. With BAT.jl, we present a modern rewrite of BAT in the Julia programming language. Through the use of a modular software design that is capable of running parallel and distributed, and by extending the tool with new sampling and integration algorithms, BAT.jl is a high-performance framework for Bayesian inference, meeting the requirements of modern data analysis.
© The Authors, published by EDP Sciences, 2020
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