The Bayesian Analysis Toolkit is a software analysis package which allows to address the main goals of a typical data analysis:
- compare model predictions with data,
- draw conclusions on the validity of the model as a representation of the data and
- extract the possible values of parameters within the context of a model.
The 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.
The BAT is implemented in C++ on top of CERN's ROOT with emphasis put on flexibility and modularity in defining models while keeping in mind the reliability and speed requirements of the numerical operations.
See doc/CREDITS
file for list of contributors to BAT.
The latest code and official BAT releases are published online at
https://github.com/bat/bat. Older BAT releases are still available from
http://mpp.mpg.de/bat/. BAT is open-source software under the LGPLv3 or later.
See doc/COPYING
and doc/LICENSE
for licensing details.
For installation instructions, see the
INSTALL.md
file or the
corresponding manual
section
reference guide: html
For additional information and contacting the authors, please consult the BAT web page at http://mpp.mpg.de/bat/. If you want to report an error or file a request, please file an issue at https://github.com/bat/bat/issues.
Directory bat/
:
doc/
: documentation about BATexamples/
: well commented example programs, seeexamples/README.md
BAT/
: BAT header filessrc/
: source files of the BAT core librarymodels
: models for specific data-analysis problems: fast fitters inbase/
and the multi-template fitter inmtf
benchmarks
: performance test suite with html outputtest
: unit teststools
: template script to generate a BAT project and build utilities
Other files distributed with BAT are part of the configuration and build system.