A program for confidence interval calculations for a Poisson process with background including systematic uncertainties: POLE 1.0 Original Research Article

A Fortran 77 routine has been developed to calculate confidence intervals with and without systematic uncertainties using a frequentist confidence interval construction with a Bayesian treatment of the systematic uncertainties. The routine can account for systematic uncertainties in the background prediction and signal/background efficiencies. The uncertainties may be separately parametrized by a Gauss, log-normal or flat probability density function (PDF), though since a Monte Carlo approach is chosen to perform the necessary integrals a generalization to other parameterizations is particularly simple. Full correlation between signal and background efficiency is optional. The ordering schemes for frequentist construction currently supported are the likelihood ratio ordering (also known as Feldman–Cousins) and Neyman ordering. Optionally, both schemes can be used with conditioning, meaning the probability density function is conditioned on the fact that the actual outcome of the background process can not have been larger than the number of observed events.