Observables in particle physics and specifically in lattice QCD calculations are often extracted from fits. Standard χ2 tests require a reliable determination of the covariance matrix and its inverse from correlated and auto-correlated data, a challenging task often leading to close-to-singular estimates. These motivate modifications of the definition of χ2 such as uncorrelated fits. We show how the goodness-of-fit measured by their p-value can still be estimated robustly for a broad class of such fits.

Bruno, M., Sommer, R. (2023). On fits to correlated and auto-correlated data. COMPUTER PHYSICS COMMUNICATIONS, 285(April 2023) [10.1016/j.cpc.2022.108643].

On fits to correlated and auto-correlated data

Bruno M.
;
2023

Abstract

Observables in particle physics and specifically in lattice QCD calculations are often extracted from fits. Standard χ2 tests require a reliable determination of the covariance matrix and its inverse from correlated and auto-correlated data, a challenging task often leading to close-to-singular estimates. These motivate modifications of the definition of χ2 such as uncorrelated fits. We show how the goodness-of-fit measured by their p-value can still be estimated robustly for a broad class of such fits.
Articolo in rivista - Articolo scientifico
Autocorrelations; Chi-squared test; Goodness of fit;
English
16-dic-2022
2023
285
April 2023
108643
none
Bruno, M., Sommer, R. (2023). On fits to correlated and auto-correlated data. COMPUTER PHYSICS COMMUNICATIONS, 285(April 2023) [10.1016/j.cpc.2022.108643].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/400694
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