BAT
swMATH ID:  67 
Software Authors:  Caldwell, Allen; Kollar, Daniel; Kröninger, Kevin 
Description:  The main goals of a typical data anaysis are to compare model predictions with data, draw conclusions on the validity of a model as a representation of the data, and to extract the values of the free parameters of a model. 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 goodnessoffit 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. 
Homepage:  https://www.mppmu.mpg.de/bat/ 
Keywords:  data analysis; Markov chain Monte Carlo 
Related Software:  HEPfit; Turing; Cuba; Optim; WinBUGS; R; PyMC; Stan; Julia; BAT.jl; eHDECAY; HIGLU; SusHi; HDECAY; OEIS; Mathematica 
Cited in:  6 Publications 
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH  Year 

BAT  the Bayesian analysis toolkit. Zbl 1197.62002 Caldwell, Allen; Kollár, Daniel; Kröninger, Kevin 
2009

all
top 5
Cited by 20 Authors
Cited in 5 Serials
2  Journal of High Energy Physics 
1  Computer Physics Communications 
1  Nuclear Physics. B 
1  Journal of Statistical Planning and Inference 
1  Journal of Applied Statistics 
Cited in 3 Fields
4  Statistics (62XX) 
3  Quantum theory (81XX) 
2  Numerical analysis (65XX) 