2006/08/25 by A. Caldwell, Allen Caldwell, K. Kröninger +1
Engineering · Mathematics · Physics and Astronomy · #Algorithm #Artificial intelligence #Bayesian probability #Computer science #Dark Matter and Cosmic Phenomena #Data mining #Electronic engineering #Engineering #Mathematics #Monte Carlo method #Neutrino Physics Research #Particle physics theoretical and experimental studies #Pattern recognition (psychology) #Physics #SIGNAL (programming language) #Sensitivity (control systems) #Statistical physics #Statistics #physics.data-an
paper · pdf · doi:10.1103/physrevd.74.092003
published as Phys.Rev.D74:092003,2006 · 15 pages, 5 figures
arxiv created 2006/08/25 · openalex publication_date 2006/11/20 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
A Bayesian analysis of the probability of a signal in the presence of background is developed, and criteria are proposed for claiming evidence for, or the discovery of a signal. The method is general and, in particular, applicable to sparsely populated spectra. Monte Carlo techniques to evaluate the sensitivity of an experiment are described. As an example, the method is used to calculate the sensitivity of the GERDA experiment to neutrinoless double beta decay.