Combined estimation for multi-measurements of branching ratio
Xiao-Xia Liu (1), Xiao-Rui Lyu (1, 3), Yong-Sheng Zhu (1, 2), ((1) University of Chinese Academy of Sciences, Beijng (2) Institute of High, Energy Physics, Beijing, (3) CAS Center for Excellence in Particle Physics,, Beijing)
TL;DR
This paper introduces a maximum likelihood approach for combining multiple measurements of a branching ratio, including cases with upper limits and systematic errors, to improve estimation accuracy.
Contribution
It presents a novel maximum likelihood method for combined estimation of branching ratios from multiple measurements, accommodating upper limits and systematic uncertainties.
Findings
Effective combined estimation of branching ratios achieved.
Bayesian credible intervals derived with and without systematic errors.
Method improves accuracy over individual measurements.
Abstract
A maximum likelihood method is used to deal with the combined estimation of multi-measurements of a branching ratio, where each result can be presented as an upper limit. The joint likelihood function is constructed using observed spectra of all measurements and the combined estimate of the branching ratio is obtained by maximizing the joint likelihood function. The Bayesian credible interval, or upper limit of the combined branching ratio, is given in cases both with and without inclusion of systematic error.
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