| Article | |
| Title | Bayesian Analysis Toolkit in Searches |
| Author(s) | Beaujean, Frederik (Munich, Max Planck Inst.) ; Caldwell, Allen (Munich, Max Planck Inst.) ; Kollár, Daniel (CERN) ; Kröninger, Kevin (U. Gottingen (main)) ; Pashapour, Shabnaz (U. Gottingen (main)) |
| Publication | Geneva : CERN, 2011 |
| Imprint | 2011-01-17 |
| Number of pages | 6 |
| In: | Proceedings of the PHYSTAT 2011 Workshop on Statistical Issues Related to Discovery Claims in Search Experiments and Unfolding, pp.209-214 |
| DOI | 10.5170/CERN-2011-006.209 |
| Subject category | Particle Physics - Experiment ; Detectors and Experimental Techniques |
| Abstract | The Bayesian Analysis Toolkit, a software package for data analysis based onBayes' theorem, is introduced. This toolkit takes advantage of Markov ChainMonte Carlo to find the full posterior probability distributions. The tool caneasily be used for parameter estimation, limit setting and error propagation.Model comparison and goodness-of-fit estimation are realized in the packagethrough well-established methods. In addition to a brief description of theBayesian Analysis Toolkit, the use of this tool in searches is described in theexample of Banff Challenge 2a problem 1. |
| Copyright/License | CC-BY-3.0 |
Corresponding record in: Inspire
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