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BAT - The Bayesian Analysis Toolkit · Around

2008

BAT - The Bayesian Analysis Toolkit

Caldwell, Allen, Kollar, Daniel, Kroeninger, Kevin

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Understand

We describe the development of a new toolkit for data analysis.

The analysis package 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.
Parameter estimation, limit setting and uncertainty propagation are implemented in a straightforward manner.

Built on

N. Metropolis et al
1953
Earlier work this paper cites.
F. James and M. Roos, Comput. Phys. Commun. 10
1975
Earlier work this paper cites.
A. Gelman and D. Rubin, Inference from iterative simulations using multiple sequences
Original
1992
Earlier work this paper cites.

Similar

See, e.g., S. Karlin and H. Taylor, A First Course in Stochastic Processes
1996
Cited alongside, same era.
R. Brun and F. Rademakers, Nucl. Instrum. Meth. A 389
1997
Cited alongside, same era.
G. D’Agostini, Bayesian Reasoning in Data Analysis - A Critical Introduction
2003
Cited alongside, same era.
http://www.mppmu.mpg.de/bat/
Cited in the paper.

Then

A. Gelman, J.B. Carlin, H. S. Stern, D. B. Rubin, Bayesian Data Analysis
2004
Later among the works it cites.
T. Hahn, Comput. Phys. Commun. 168
2005
Later among the works it cites.
A. Caldwell and K. Kröninger, Phys. Rev. D 74
2006
Later among the works it cites.

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