A Bayesian approach to evaluate confidence intervals in counting experiments with background
arXiv:1105.3041 · doi:10.1016/j.nima.2011.05.023
Abstract
In this paper we propose a procedure to evaluate Bayesian confidence intervals in counting experiments where both signal and background fluctuations are described by the Poisson statistics. The results obtained when the method is applied to the calculation of upper limits will also be illustrated.
19 pages, 6 figures
References in corpus (4)
- A Unified Approach to the Classical Statistical Analysis of Small Signals
- Limits and Confidence Intervals in the Presence of Nuisance Parameters
- Confidence Intervals and Upper Bounds for Small Signals in the Presence of Background Noise
- Interval estimation in the presence of nuisance parameters. 1. Bayesian approach
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