Performance-based Weighting

Performance-Based Weighting is a method of assigning weights to individual forecasters or models in expert judgment elicitation and forecast combination, wherein the weights are determined by the past predictive performance of each forecaster or model, with higher-performing sources receiving greater weight.

38

Publications

1.9K

Citations

96

Authors

71

Institutions

Publications per year

2017–2026

13

Variants

Performance-weighted Combination

Authors

96

  1. RC
    Roger Cooke

    University of California, San Francisco, United States

    3 publications · 236 citations

    3

    h-index

  2. FG
    Filippo Giorgi

    The Abdus Salam International Centre for Theoretical Physics (ICTP), Italy

    2 publications · 522 citations

    2

    h-index

  3. MA
    Mark A. Burgman

    The University of Melbourne, Australia

    2 publications · 76 citations

    2

    h-index

  4. AM
    Anca M. Hanea

    The University of Melbourne, Australia

    2 publications · 76 citations

    2

    h-index

  5. RK
    R.L. Kress

    University of Tennessee at Knoxville, United States

    1 publications · 22 citations

    1

    h-index

1–5 of 96

Venues

  1. Risk Analysis

    2 publications · 76 citations

    2

    h-index

  2. SSRN Electronic Journal

    Repository · 2 publications · 32 citations

    2

    h-index

  3. 2

    h-index

  4. Reliability Engineering & System Safety

    2 publications · 204 citations

    2

    h-index

  5. Climate Research

    2 publications · 522 citations

    2

    h-index

1–5