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CISS
2011
IEEE

Improving aggregated forecasts of probability

12 years 7 months ago
Improving aggregated forecasts of probability
—The Coherent Approximation Principle (CAP) is a method for aggregating forecasts of probability from a group of judges by enforcing coherence with minimal adjustment. This paper explores two methods to further improve the forecasting accuracy within the CAP framework and proposes practical algorithms that implement them. These methods allow flexibility to add fixed constraints to the coherentization process and compensate for the psychological bias present in probability estimates from human judges. The algorithms were tested on a data set of nearly half a million probability estimates of events related to the 2008 U.S. presidential election (from about 16000 judges). The results show that both methods improve the stochastic accuracy of the aggregated forecasts compared to using simple CAP.
Guanchun Wang, Sanjeev R. Kulkarni, H. Vincent Poo
Added 18 Aug 2011
Updated 18 Aug 2011
Type Journal
Year 2011
Where CISS
Authors Guanchun Wang, Sanjeev R. Kulkarni, H. Vincent Poor, Daniel N. Osherson
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