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A Note on the Aggregation of Event Probabilities

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  • Stephen C. Hora

Abstract

In this article, multiple forecasts given as probabilities of events are aggregated using two assumptions: calibration and conditional independence. The forecasts are treated as data and the aggregation is based on Bayes's theorem. A measure of discrimination is given and the behavior of the aggregated posterior probability is examined as the number of forecasters grows without bound. The work is motivated by recent research efforts employing large numbers of individual forecasts.

Suggested Citation

  • Stephen C. Hora, 2013. "A Note on the Aggregation of Event Probabilities," Risk Analysis, John Wiley & Sons, vol. 33(5), pages 909-914, May.
    • Handle: RePEc:wly:riskan:v:33:y:2013:i:5:p:909-914
    DOI: 10.1111/j.1539-6924.2012.01889.x
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    1. Robert F. Bordley & Ronald W. Wolff, 1981. "Note---On the Aggregation of Individual Probability Estimates," Management Science, INFORMS, vol. 27(8), pages 959-964, August.
    2. Stephen C. Hora, 2004. "Probability Judgments for Continuous Quantities: Linear Combinations and Calibration," Management Science, INFORMS, vol. 50(5), pages 597-604, May.
    3. Robert L. Winkler, 1981. "Combining Probability Distributions from Dependent Information Sources," Management Science, INFORMS, vol. 27(4), pages 479-488, April.
    4. Stephen C. Hora, 2010. "An Analytic Method for Evaluating the Performance of Aggregation Rules for Probability Densities," Operations Research, INFORMS, vol. 58(5), pages 1440-1449, October.
    5. Robert F. Bordley, 1982. "A Multiplicative Formula for Aggregating Probability Assessments," Management Science, INFORMS, vol. 28(10), pages 1137-1148, October.
    6. Peter A. Morris, 1977. "Combining Expert Judgments: A Bayesian Approach," Management Science, INFORMS, vol. 23(7), pages 679-693, March.
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    Cited by:

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