Acero, MA;
Acharya, B;
Adamson, P;
Aliaga, L;
Anfimov, N;
Antoshkin, A;
Arrieta-Diaz, E;
... The NOvA collaboration, .; + view all
(2025)
Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment.
Journal of Instrumentation
, 20
, Article T02001. 10.1088/1748-0221/20/02/T02001.
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Abstract
Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain conditions. These conditions, such as nested hypotheses and unbounded parameters, are often violated in neutrino oscillation measurements and other experimental scenarios. Monte Carlo methods can address these issues, albeit at increased computational cost. In the presence of nuisance parameters, however, the best way to implement a Monte Carlo method is ambiguous. This paper documents the method selected by the NOvA experiment, the profile construction. It presents the toy studies that informed the choice of method, details of its implementation, and tests performed to validate it. It also includes some practical considerations which may be of use to others choosing to use the profile construction.
| Type: | Article |
|---|---|
| Title: | Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1088/1748-0221/20/02/T02001 |
| Publisher version: | https://doi.org/10.1088/1748-0221/20/02/T02001 |
| Language: | English |
| Additional information: | This version is the author-accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Instruments & Instrumentation, Analysis and statistical methods, Computing (architecture farms, GRID for recording storage, archiving, and distribution of data), SYSTEMATIC UNCERTAINTIES |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10220794 |
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