Generalized Linear Model Averaging

Generalized Linear Model Averaging is a statistical inference framework that extends Bayesian Model Averaging by integrating generalized linear models to account for non-normal response distributions, thereby enabling robust uncertainty quantification and parameter estimation across competing models in the presence of model specification uncertainty.

12

Publications

751

Citations

37

Authors

28

Institutions

Publications per year

2017–2026

3

Authors

37

  1. AC
    Ali Charkhi

    KU Leuven, Belgium

    2 publications · 38 citations

    2

    h-index

  2. GZ
    Guohua Zou

    Chinese Academy of Sciences, China

    2 publications · 184 citations

    2

    h-index

  3. BE
    Bruce E. Hansen

    University of Wisconsin–Madison, United States

    2 publications · 38 citations

    2

    h-index

  4. GC
    Gerda Claeskens

    KU Leuven, Belgium

    2 publications · 38 citations

    2

    h-index

  5. MA
    Michael A. Proschan

    National Institute of Allergy and Infectious Diseases, United States

    1 publications · 114 citations

    1

    h-index

1–5 of 37

Venues

  1. SSRN Electronic Journal

    Repository · 1 publications · 19 citations

    1

    h-index

  2. Statistica Sinica

    1 publications · 19 citations

    1

    h-index

  3. Biometrics

    1 publications · 114 citations

    1

    h-index

  4. Journal of Econometrics

    1 publications · 15 citations

    1

    h-index

  5. Genetics

    1 publications · 246 citations

    1

    h-index

1–5