2011/10/09 by The NNPDF Collaboration, Richard D. Ball, Ball, Richard D. +18
Physics and Astronomy · #Data Analysis #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #Particle physics theoretical and experimental studies #Statistics and Probability (physics.data-an) #hep-ph #physics.data-an
paper · pdf · doi:10.48550/arxiv.1110.1863
11 pages, 8 figures, presented by Stefano Forte at PHYSTAT 2011 (to be published in the proceedings)
arxiv created 2011/10/09 · openalex publication_date 2011/10/09 · arxiv updated 2011/10/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We discuss the statistical properties of parton distributions within the framework of the NNPDF methodology. We present various tests of statistical consistency, in particular that the distribution of results does not depend on the underlying parametrization and that it behaves according to Bayes' theorem upon the addition of new data. We then study the dependence of results on consistent or inconsistent datasets and present tools to assess the consistency of new data. Finally we estimate the relative size of the PDF uncertainty due to data uncertainties, and that due to the need to infer a functional form from a finite set of data.