Weighted Model Averaging

Weighted Model Averaging is a Bayesian inference technique that belongs to the class of model averaging methods, distinguished by its use of posterior model probabilities as weights to combine predictions or estimates from multiple candidate models in proportion to their relative evidential support.

43

Publications

4.5K

Citations

121

Authors

82

Institutions

Publications per year

2017–2026

11

Variants

Wma

Authors

121

  1. HJ
    H. J. B. Birks

    University of Bergen, Norway

    4 publications · 1.6K citations

    4

    h-index

  2. JP
    John P. Smol

    Queen's University, Canada

    4 publications · 252 citations

    4

    h-index

  3. JM
    J. M. Line

    University of Cambridge, United Kingdom

    3 publications · 1.4K citations

    3

    h-index

  4. CJ
    Cajo J. F. ter Braak

    Wageningen University & Research, Netherlands

    2 publications · 797 citations

    2

    h-index

  5. MA
    Moetasim Ashfaq

    Oak Ridge National Laboratory, United States

    2 publications · 74 citations

    2

    h-index

1–5 of 121

Venues

  1. Journal of Paleolimnology

    5 publications · 571 citations

    5

    h-index

  2. Artificial Intelligence

    2 publications · 397 citations

    2

    h-index

  3. 1

    h-index

  4. Freshwater Biology

    1 publications · 209 citations

    1

    h-index

  5. 1

    h-index

1–5