Calibrated Forecasting

Calibrated Forecasting is a probabilistic forecasting method that belongs to the class of forecasting techniques in which the predicted probability distributions are adjusted so that the frequency of observed outcomes matches the predicted probabilities, thereby ensuring statistical consistency between forecasts and realizations.

42

Publications

2.4K

Citations

92

Authors

74

Institutions

Publications per year

2017–2026

9

Authors

92

  1. DP
    Dean P. Foster

    University of Pennsylvania, United States

    3 publications · 404 citations

    3

    h-index

  2. RS
    Rann Smorodinsky

    Technion – Israel Institute of Technology, Israel

    2 publications · 145 citations

    2

    h-index

  3. SE
    Stefano Ermon

    Stanford University, United States

    2 publications · 25 citations

    2

    h-index

  4. AP
    A. P. Dawid

    University College London, United Kingdom

    2 publications · 710 citations

    2

    h-index

  5. RV
    Rakesh Vohra

    Northwestern University, United States

    2 publications · 467 citations

    2

    h-index

1–5 of 92

Venues

  1. SSRN Electronic Journal

    Repository · 3 publications · 51 citations

    3

    h-index

  2. Games and Economic Behavior

    3 publications · 444 citations

    3

    h-index

  3. International Journal of Forecasting

    3 publications · 55 citations

    3

    h-index

  4. 2

    h-index

  5. Mathematics of Operations Research

    2 publications · 119 citations

    2

    h-index

1–5