Limits, discovery and cut optimization for a Poisson process with uncertainty in background and signal efficiency: TRolke 2.0

Abstract

A C++ class was written for the calculation of frequentist confidence intervals using the profile likelihood method. Seven combinations of Binomial, Gaussian, Poissonian and Binomial uncertainties are implemented. The package provides routines for the calculation of upper and lower limits, sensitivity and related properties. It also supports hypothesis tests which take uncertainties into account. It can be used in compiled C++ code, in Python or interactively via the ROOT analysis framework.

18 pages, 1 figure

References in corpus (2)

• Limits and Confidence Intervals in the Presence of Nuisance Parameters
• Comment on "Including Systematic Uncertainties in Confidence Interval Construction for Poisson Statistics"

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