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Properization: constructing proper scoring rules via Bayes acts

Brehmer, Jonas R.; Gneiting, Tilmann

Abstract:
Scoring rules serve to quantify predictive performance. A scoring rule is proper if truth telling is an optimal strategy in expectation. Subject to customary regularity conditions, every scoring rule can be made proper, by applying a special case of the Bayes act construction studied by Grünwald and Dawid (2004) and Dawid (2007), to which we refer as properization. We discuss examples from the recent literature and apply the construction to create new types, and reinterpret existing forms, of proper scoring rules and consistent scoring functions. In an abstract setting, we formulate sufficient conditions under which Bayes acts exist and scoring rules can be made proper.



Zugehörige Institution(en) am KIT Institut für Stochastik (STOCH)
Publikationstyp Forschungsbericht/Preprint
Publikationsmonat/-jahr 06.2020
Sprache Englisch
Identifikator KITopen-ID: 1000124917
Vorab online veröffentlicht am 22.02.2019
Nachgewiesen in arXiv
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