Speaker
Dr
Kevin Kroeninger
(University of Goettingen)
Description
BAT - a complex Markov chain Monte Carlo application
The tutorial will give an introduction to the Bayesian Analysis
Toolkit (BAT), a C++ tool for Bayesian inference. The software is
based on algorithms for sampling, optimization and integration where
the key algorithm is Markov Chain Monte Carlo. Interfaces to existing
software tools exists, e.g., the ROOT implementation of Minuit, and
the Cuba library. A simple physics example will be discussed and
formulated as a statistical model in BAT. The first steps will include
the calculation of marginal distributions and uncertainty
propagation. The example will also be used to explain the basic
functionalities of BAT.
