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dc.contributor.authorHeld, L.*
hal.structure.identifier
dc.contributor.authorRufibach, Kaspar*
hal.structure.identifier
dc.contributor.authorBalabdaoui, Fadoua*
dc.date.accessioned2013-10-14T08:28:17Z
dc.date.available2013-10-14T08:28:17Z
dc.date.issued2010
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/11814
dc.language.isoenen
dc.subjectCalibrationen
dc.subjectContinuous predictionsen
dc.subjectCrossvalidationen
dc.subjectRegressionen
dc.subjectScoring rulesen
dc.subject.ddc519en
dc.titleA Score Regression Approach to Assess Calibration of Continuous Probabilistic Predictionsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenCalibration, the statistical consistency of forecast distributions and the observations, is a central requirement for probabilistic predictions. Calibration of continuous forecasts is typically assessed using the probability integral transform histogram. In this article, we propose significance tests based on scoring rules to assess calibration of continuous predictive distributions. For an ideal normal forecast we derive the first two moments of two commonly used scoring rules: the logarithmic and the continuous ranked probability score. This naturally leads to the construction of two unconditional tests for normal predictions. More generally, we propose a novel score regression approach, where the individual scores are regressed on suitable functions of the predictive variance. This conditional approach is applicable even for certain nonnormal predictions based on the Dawid–Sebastiani score. Two case studies illustrate that the score regression approach has typically more power in detecting miscalibrated forecasts than the other approaches considered, including a recently proposed technique based on conditional exceedance probability curves.en
dc.relation.isversionofjnlnameBiometrics
dc.relation.isversionofjnlvol66en
dc.relation.isversionofjnlissue4en
dc.relation.isversionofjnldate2010
dc.relation.isversionofjnlpages1295-1305en
dc.relation.isversionofdoihttp://dx.doi.org/10.1111/j.1541-0420.2010.01406.xen
dc.relation.isversionofjnlpublisherWileyen
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingprintnonen
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