Limits, discovery and cut optimization for a Poisson process with uncertainty in background and signal efficiency: TRolke 2.0
2010 (English)In: Computer Physics Communications, ISSN 0010-4655, E-ISSN 1879-2944, Vol. 181, no 3, 683-686 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2010. Vol. 181, no 3, 683-686 p.
Confidence intervals, Hypothesis tests, Systematic uncertainties, Poisson statistics
Research subject Physics
IdentifiersURN: urn:nbn:se:su:diva-50061DOI: 10.1016/j.cpc.2009.11.001ISI: 000274576800021OAI: oai:DiVA.org:su-50061DiVA: diva2:382742
authorCount :42011-01-032010-12-212011-01-03Bibliographically approved