Improved iterative Bayesian unfolding

Details Improved iterative Bayesian unfolding Improved iterative Bayesian unfolding

2010-10-04

arxiv.org/abs/1010.0632v1

Physics

Data Analysis, Statistics and Probability

31 pages, 7 figures, presented at the Alliance Workshop on Unfolding and Data Correction (Hamburg, Germany, 27-28 May 2010). S

Scientific paper

This paper reviews the basic ideas behind a Bayesian unfolding published some years ago and improves their implementation. In particular, uncertainties are now treated at all levels by probability density functions and their propagation is performed by Monte Carlo integration. Thus, small numbers are better handled and the final uncertainty does not rely on the assumption of normality. Theoretical and practical issues concerning the iterative use of the algorithm are also discussed. The new program, implemented in the R language, is freely available, together with sample scripts to play with toy models.

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