A Measure of the Goodness of Fit in Unbinned Likelihood Fits

dc.creatorRaja, Rajendran
dc.date2002-07-22
dc.date2002-07-30
dc.date.accessioned2026-07-07T05:47:52Z
dc.date.available2026-07-07T05:47:52Z
dc.descriptionMaximum likelihood fits to data can be done using binned data (histograms) and unbinned data. With binned data, one gets not only the fitted parameters but also a measure of the goodness of fit. With unbinned data, currently, the fitted parameters are obtained but no measure of goodness of fit is available. This remains, to date, an unsolved problem in statistics. Using Bayes theorem and likelihood ratios, we provide a method by which both the fitted quantities and a measure of the goodness of fit are obtained for unbinned likelihood fits, as well as errors in the fitted quantities. We provide an ansatz for determining Bayesian a priori probabilities.
dc.description26 pages, 8 figures
dc.identifierhttps://arxiv.org/abs/physics/0207083
dc.identifierhttp://arxiv.org/abs/physics/0207083
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/84819
dc.subjectData Analysis, Statistics and Probability
dc.subjectGeneral Physics
dc.titleA Measure of the Goodness of Fit in Unbinned Likelihood Fits
dc.typetext

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