This C++ version of BAT is still being maintained, but addition of new features is unlikely. Check out our new incarnation, BAT.jl, the Bayesian analysis toolkit in Julia. In addition to Metropolis-Hastings sampling, BAT.jl supports Hamiltonian Monte Carlo (HMC) with automatic differentiation, automatic prior-based parameter space transformations, and much more. See the BAT.jl documentation.
The main goals of a typical data anaysis are to
The Bayesian Analysis Toolkit, BAT, is a software package which addresses the points above. It is designed to help solve statistical problems encountered in Bayesian inference. BAT 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 and enables straightforward parameter estimation, limit setting and uncertainty propagation.
BAT is implemented in C++ and allows for a flexible definition of mathematical models and applications while keeping in mind the reliability and speed requirements of the numerical operations. It provides a set of algorithms for numerical integration, optimization and error propagation. Predefined models exist for standard cases. In addition, methods to judge the goodness-of-fit of a model are implemented. An interface to ROOT allows for further analysis and graphical display of results. BAT can also be run from within RooStats analysis.
Release candidate. The first release candidate for the upcoming version 1.0 has been released over at github. It provides major changes and improvements.
BAT version 0.9.4.1 released. Bugfix release fixes installation on mac os with root6.
BAT version 0.9.4 released. Get it from github.
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