On fits to correlated and auto-correlated data

Sommer, Rainer; Bruno, Mattia

doi:10.1016/j.cpc.2022.108643

Journal Article

PUBDB-2022-04925

On fits to correlated and auto-correlated data

Sommer, R. (Corresponding author)DESY* ; Bruno, M. (Corresponding author)Extern*

2023
North Holland Publ. Co. Amsterdam

Computer physics communications 285, 108643 (2023) [10.1016/j.cpc.2022.108643]

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Please use a persistent id in citations: doi:10.1016/j.cpc.2022.108643 doi:10.3204/PUBDB-2022-04925

Report No.: DESY-22-154; arXiv:2209.14188

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.

Keyword(s): lattice field theory ; covariance ; Chi-squared test ; Goodness of fit ; Autocorrelations

Classification:

ddc:530

Note: 15 pages, 4 figures

Contributing Institute(s):

Zeuthen Particle PhysicsTheory (Z_ZPPT)

Research Program(s):

611 - Fundamental Particles and Forces (POF4-611) (POF4-611)

Experiment(s):

No specific instrument

Appears in the scientific report 2023

Database coverage:
Medline

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