Axiomatic Characterization of the Quadratic Scoring Rule
In the evaluation of experiments often the problem arises how to compare the predictive success of competing probabilistic theories. The quadratic soring rule can be used for this purpose. Originally this rule has been proposed as an incentive compatible elicitation method for probabilistic expert judgements. It is shown that up to a positive linear transformation, the quadratic scoring rule is characterized by five desirable properties.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||Oct 1996|
|Date of revision:|
|Contact details of provider:|| Postal: Bonn Graduate School of Economics, University of Bonn, Adenauerallee 24 - 26, 53113 Bonn, Germany|
Fax: +49 228 73 6884
Web page: http://www.bgse.uni-bonn.de
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Selten,Reinhard, .
"Properties of a measure of predictive succes,"
Discussion Paper Serie B
130, University of Bonn, Germany.
- Daniel Friedman, 1983. "Effective Scoring Rules for Probabilistic Forecasts," Management Science, INFORMS, vol. 29(4), pages 447-454, April.
- James E. Matheson & Robert L. Winkler, 1976. "Scoring Rules for Continuous Probability Distributions," Management Science, INFORMS, vol. 22(10), pages 1087-1096, June.
When requesting a correction, please mention this item's handle: RePEc:bon:bonsfb:390. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (BGSE Office)
If references are entirely missing, you can add them using this form.