Bayesian credible interval construction for Poisson statistics
Yong-Sheng Zhu
TL;DR
This paper presents a method for constructing Bayesian credible intervals for Poisson-distributed data, including background and uncertainties, with an implementation routine.
Contribution
It introduces a new Bayesian interval construction method for Poisson data with background and uncertainties, and provides a Fortran implementation.
Findings
Effective Bayesian credible intervals for Poisson data with background.
Inclusion of systematic uncertainties in interval construction.
Availability of BPOCI routine for practical calculations.
Abstract
The construction of the Bayesian credible (confidence) interval for a Poisson observable including both the signal and background with and without systematic uncertainties is presented. Introducing the conditional probability satisfying the requirement of the background not larger than the observed events to construct the Bayesian credible interval is also discussed. A Fortran routine, BPOCI, has been developed to implement the calculation.
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