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Combining multiple probability predictions using a simple logit model

Author

Listed:
  • Satopää, Ville A.
  • Baron, Jonathan
  • Foster, Dean P.
  • Mellers, Barbara A.
  • Tetlock, Philip E.
  • Ungar, Lyle H.

Abstract

This paper begins by presenting a simple model of the way in which experts estimate probabilities. The model is then used to construct a likelihood-based aggregation formula for combining multiple probability forecasts. The resulting aggregator has a simple analytical form that depends on a single, easily-interpretable parameter. This makes it computationally simple, attractive for further development, and robust against overfitting. Based on a large-scale dataset in which over 1300 experts tried to predict 69 geopolitical events, our aggregator is found to be superior to several widely-used aggregation algorithms.

Suggested Citation

  • Satopää, Ville A. & Baron, Jonathan & Foster, Dean P. & Mellers, Barbara A. & Tetlock, Philip E. & Ungar, Lyle H., 2014. "Combining multiple probability predictions using a simple logit model," International Journal of Forecasting, Elsevier, vol. 30(2), pages 344-356.
    • Handle: RePEc:eee:intfor:v:30:y:2014:i:2:p:344-356
    DOI: 10.1016/j.ijforecast.2013.09.009
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    References listed on IDEAS

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