Tailored scoring rules for probabilities

Decision Analysis

Volumn 8, Issue 4, 2011, Pages 256-268

  Johnstone, David J ^a   Jose, Victor Richmond R ^b   Winkler, Robert L ^c  

^a UNIVERSITY OF SYDNEY   (Australia)

^b GEORGETOWN UNIVERSITY   (United States)

^c DUKE UNIVERSITY   (United States)

Author keywords

Decision analysis; Incentives; Probability evaluation; Probability forecasts; Scoring rules; Utility

Indexed keywords

EID: 83755187873     PISSN: 15458490     EISSN: 15458504     Source Type: Journal    
DOI: 10.1287/deca.1110.0216     Document Type: Article

References (24)

1. Bickel, J. E. 2006. Some determinants of corporate risk aversion. Decision Anal. 3(4) 233-251.
2. Bickel, J. E. 2007. Some comparisons among quadratic, spherical, and logarithmic scoring rules. Decision Anal. 4(2) 49-65.
3. Brier, G. W. 1950. Verification of forecasts expressed in terms of probabilities. Monthly Weather Rev. 78(1) 1-3.
4. Dawid, A. P. 2007. The geometry of proper scoring rules. Ann. Inst. Statist. Math. 59(1) 77-93.
5. Dirkzwager, A. 1996. Testing with personal probabilities: 11-year-olds can correctly estimate their personal probabilities. Educational Psych. Measurement 56(6) 957-971.
6. Gneiting, T. 2008. Editorial: Probabilistic forecasting. J. Royal Statist. Soc. A. 171(2) 319-321.
7. Gneiting, T., A. Raftery. 2007. Strictly proper scoring rules, prediction, and estimation. J. Amer. Statist. Assoc. 102(477) 359-378.
8. Johnstone, D. J. 2007. The parimutuel Kelly probability scoring rule. Decision Anal. 4(2) 66-75.
9. Johnstone, D. J. 2011. Economic interpretation of probabilities estimated by maximum likelihood or score. Management Sci. 57(2) 308-314.
10. Jose, V. R. R., R. F. Nau, R. L. Winkler. 2008. Scoring rules, generalized entropy, and utility maximization. Oper. Res. 56(5) 1148-1157.
11. Jose, V. R. R., R. F. Nau, R. L. Winkler. 2009. Sensitivity to distance and baseline distributions in forecast evaluation. Management Sci. 55(4) 582-590.
12. Lopez, J. A. 2001. Evaluating the predictive accuracy of volatility models. J. Forecasting 20(2) 87-109. (Pubitemid 32370442)
13. McCarthy, J. 1956. Measures of the value of information. Proc. Natl. Acad. Sci. USA 42(9) 654-655.
14. Murphy, A. H. 1966. A note on the utility of probabilistic predictions and the probability score in the cost-loss ratio decision situation. J. Appl. Meteorol. 5(4) 534-537.
15. Murphy, A. H. 1972a. Scalar and vector partitions of the probability score: Part I. Two-state situation. J. Appl. Meteorol. 11(2) 273-282.
16. Murphy, A. H. 1972b. Scalar and vector partitions of the probability score: Part II. N-state situation. J. Appl. Meteorol. 11(8) 1183-1192.
17. Murphy, A. H. 1973. Hedging and skill scores for probability forecasts. J. Appl. Meteorol. 12(1) 215-223.
18. Offerman, T., J. Sonnemans, G. van de Kuilen, P. P. Wakker. 2009. A truth serum for non-Bayesians: Correcting proper scoring rules for risk attitudes. Rev. Econom. Stud. 76(4) 1461-1489.
19. O'Hagan, A., C. E. Buck, A. Daneshkhah, J. R. Eiser, P. H. Garthwaite, D. J. Jenkinson, J. E. Oakley, T. Rakow. 2006. Uncertain Judgments: Eliciting Experts' Probabilities. John Wiley & Sons, Chichester, UK.
20. Savage, L. J. 1971. Elicitation of personal probabilities and expectations. J. Amer. Statist. Assoc. 66(336) 783-801.
21. Winkler, R. L. 1969. Scoring rules and the evaluation of probability assessors. J. Amer. Statist. Assoc. 64(327) 1073-1078.
22. Winkler, R. L. 1994. Evaluating probabilities: Asymmetric scoring rules. Management Sci. 40(11) 1395-1405.
23. Winkler, R. L. 1996. Scoring rules and the evaluation of probabilities. Test 5(1) 1-60.
24. Yates, J. F. 1982. External correspondence: Decompositions of the mean probability score. Organ. Behav. Human Performance 30(1) 132-156.