Proper Scoring Rules

Proper Scoring Rules is a scoring function used to evaluate probabilistic forecasts that elicits honest and calibrated predictions by ensuring the expected score is minimized only when the predicted probability distribution matches the true distribution.

185

Publications

21.5K

Citations

344

Authors

208

Institutions

Publications per year

2017–2026

49

Authors

344

  1. RL
    Robert L. Winkler

    Duke University, United States

    8 publications · 799 citations

    8

    h-index

  2. AH
    Allan H. Murphy

    Oregon State University, United States

    7 publications · 721 citations

    7

    h-index

  3. TG
    Tilmann Gneiting

    University of Washington, United States

    6 publications · 7.4K citations

    6

    h-index

  4. TL
    Thordis L. Thorarinsdottir

    Norwegian Computing Center, Norway

    4 publications · 244 citations

    4

    h-index

  5. FK
    Fabian Krüger

    Karlsruhe Institute of Technology, Germany

    4 publications · 274 citations

    4

    h-index

1–5 of 344

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 213 citations

    10

    h-index

  2. Decision Analysis

    8 publications · 475 citations

    8

    h-index

  3. Management Science

    6 publications · 343 citations

    6

    h-index

  4. Journal of applied meteorology

    5 publications · 1.1K citations

    5

    h-index

  5. SSRN Electronic Journal

    Repository · 4 publications · 63 citations

    4

    h-index

1–5