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Evaluating probability forecasts in terms of refinement and strictly proper scoring rules
Author(s) -
Krämer Walter
Publication year - 2006
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.976
Subject(s) - scoring rule , computer science , econometrics , mathematical economics , mathematics , machine learning
This note gives an easily verified necessary and sufficient condition for one probability forecaster to empirically outperform another one in terms of all strictly proper scoring rules. Copyright © 2006 John Wiley & Sons, Ltd.