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000482723 1001_ $$0P:(DE-H253)PIP1003629$$aSommer, Rainer$$b0$$eCorresponding author
000482723 245__ $$aOn fits to correlated and auto-correlated data
000482723 260__ $$aAmsterdam$$bNorth Holland Publ. Co.$$c2023
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000482723 520__ $$aObservables in particle physics and specifically in lattice QCD calculations    are often extracted from fits.    Standard $\chi^2$ tests require a reliable determination of the covariance    matrix and its inverse from correlated and auto-correlated data,    a challenging task often    leading to close-to-singular estimates. These motivate modifications of the definition of $\chi^2$ such as uncorrelated fits.     We show how the goodness-of-fit measured by their p-value can    still be estimated robustly for a broad class of such fits.
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000482723 650_7 $$2INSPIRE$$alattice field theory
000482723 650_7 $$2INSPIRE$$acovariance
000482723 650_7 $$2autogen$$aChi-squared test
000482723 650_7 $$2autogen$$aGoodness of fit
000482723 650_7 $$2autogen$$aAutocorrelations
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000482723 7001_ $$0P:(DE-H253)PIP1018357$$aBruno, Mattia$$b1$$eCorresponding author
000482723 773__ $$0PERI:(DE-600)1466511-6$$a10.1016/j.cpc.2022.108643$$gVol. 285, p. 108643 -$$p108643$$tComputer physics communications$$v285$$x0010-4655$$y2023
000482723 7870_ $$0PUBDB-2022-05083$$aBruno, Mattia et.al.$$d2022$$iIsParent$$rarXiv:2209.14188 ; DESY-22-154$$tOn fits to correlated and auto-correlated data
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