Bayesian Model Averaging

Bayesian Model Averaging is a statistical inference method that belongs to the class of Bayesian model selection techniques, distinguished by its integration of posterior inferences over multiple candidate models weighted by their respective posterior probabilities, thereby accounting for model uncertainty in parameter estimation and prediction.

673

Publications

62K

Citations

1.4K

Authors

769

Institutions

Publications per year

2017–2026

212

Authors

1.4K

  1. AE
    Adrian E. Raftery

    University of Washington, United States

    25 publications · 10.1K citations

    22

    h-index

  2. EW
    Eric‐Jan Wagenmakers

    University of Amsterdam, Netherlands

    14 publications · 1.3K citations

    13

    h-index

  3. QF
    Quentin F. Gronau

    University of Amsterdam, Netherlands

    13 publications · 1.2K citations

    12

    h-index

  4. FT
    Frank T.‐C. Tsai

    Louisiana State University, United States

    12 publications · 553 citations

    12

    h-index

  5. MF
    Mark F. J. Steel

    University of Warwick, United Kingdom

    11 publications · 3.2K citations

    11

    h-index

1–5 of 1.4K

Venues

  1. Water Resources Research

    24 publications · 2.8K citations

    22

    h-index

  2. Journal of Hydrology

    21 publications · 1.5K citations

    19

    h-index

  3. 18

    h-index

  4. SSRN Electronic Journal

    Repository · 29 publications · 1K citations

    18

    h-index

  5. Journal of Applied Econometrics

    14 publications · 2.4K citations

    12

    h-index

1–5