On fits to correlated and auto-correlated data

Abstract

Observables in particle physics and specifically in lattice QCD calculations are often extracted from fits. Standard ${\chi }^2$ 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 ${\chi }^2$ 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.

15 pages, 4 figures, matching published version

References in corpus (2)

• Critical slowing down and error analysis in lattice QCD simulations
• Form factors of $B\to \pi \ell \nu$ and a determination of $|V_{ub}|$ with Möbius domain-wall-fermions

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