Accessibility navigation


Contrasting probabilistic scoring rules

Machete, R. (2013) Contrasting probabilistic scoring rules. Journal of Statistical Planning and Inference, 143 (10). pp. 1781-1790. ISSN 0378-3758

Full text not archived in this repository.

To link to this item DOI: 10.1016/j.jspi.2013.05.012

Abstract/Summary

There are several scoring rules that one can choose from in order to score probabilistic forecasting models or estimate model parameters. Whilst it is generally agreed that proper scoring rules are preferable, there is no clear criterion for preferring one proper scoring rule above another. This manuscript compares and contrasts some commonly used proper scoring rules and provides guidance on scoring rule selection. In particular, it is shown that the logarithmic scoring rule prefers erring with more uncertainty, the spherical scoring rule prefers erring with lower uncertainty, whereas the other scoring rules are indifferent to either option.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
ID Code:32679
Publisher:Elsevier

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation