Uncertainty components in profile likelihood fits
Andr\'es Pinto, Zhibo Wu, Fabrice Balli, Nicolas Berger, Maarten, Boonekamp, \'Emilien Chapon, Tatsuo Kawamoto, Bogdan Malaescu

TL;DR
This paper clarifies the distinction between impact and actual uncertainty components in profile-likelihood fits, proposing methods to accurately determine these components for better uncertainty propagation in high-energy physics analyses.
Contribution
It introduces new methods to identify true uncertainty components in profile-likelihood fits, improving the accuracy of uncertainty decomposition beyond impact estimates.
Findings
Impacts are not equivalent to actual uncertainty components.
Methods are established to determine true uncertainty components.
Enhanced accuracy in uncertainty propagation for physics analyses.
Abstract
When a measurement of a physical quantity is reported, the total uncertainty is usually decomposed into statistical and systematic uncertainties. This decomposition is not only useful to understand the contributions to the total uncertainty, but also required to propagate these contributions in subsequent analyses, such as combinations or interpretation fits including results from other measurements or experiments. In profile-likelihood fits, widely applied in high-energy physics analyses, contributions of systematic uncertainties are routinely quantified using "impacts", which are not adequate for such applications. We discuss the difference between impacts and actual uncertainty components, and establish methods to determine the latter in a wide range of statistical models.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNuclear Physics and Applications · Particle Detector Development and Performance · Radioactive Decay and Measurement Techniques
