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Tests of goodness of fit to multiple data sets
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We propose a new and rather stringent criterion for testing the goodness of fit between a theory and experiment. It is motivated by the paradox that the criterion on \chi^2 for testing a theory is much weaker than the criterion for finding the best fit value of a parameter in the theory. We present a method by which the stronger parameter-fitting criterion can be applied to subsets of data in a global fit.
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Cited by 2 Pith papers
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New CTEQ global analysis of quantum chromodynamics with high-precision data from the LHC
New CT18 PDFs at NLO and NNLO from global fit to HERA plus LHC jet, Drell-Yan, top-pair and Z data, with Hessian errors, Lagrange-multiplier studies, and alternate sets for data tensions and scale choices.
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