Hierarchical Bayesian Estimation

Hierarchical Bayesian Estimation is a statistical inference method that belongs to the class of Bayesian estimation techniques, distinguished by its use of multiple levels of prior distributions to model parameters and their dependencies across groups or layers of data.

1.1K

Publications

94K

Citations

6.4K

Authors

1.6K

Institutions

Publications per year

2017–2026

439

Publications

1.1K

1–5 of 1.1K

Authors

6.4K

  1. BP
    Bradley P. Carlin

    University of Minnesota, United States

    16 publications · 1.1K citations

    14

    h-index

  2. ME
    Majid Ezzati

    Imperial College London, United Kingdom

    12 publications · 17.4K citations

    12

    h-index

  3. CP
    Costas Papadimitriou

    University of Thessaly, Greece

    9 publications · 624 citations

    9

    h-index

  4. DL
    Duncan Lee

    University of Glasgow, United Kingdom

    9 publications · 505 citations

    9

    h-index

  5. SF
    Seth Flaxman

    Imperial College London, United Kingdom

    8 publications · 2.5K citations

    8

    h-index

1–5 of 6.4K

Venues

  1. Journal of the American Statistical Association

    35 publications · 2.1K citations

    23

    h-index

  2. PLoS ONE

    26 publications · 1.6K citations

    19

    h-index

  3. Statistics in Medicine

    24 publications · 1.4K citations

    18

    h-index

  4. Monthly Notices of the Royal Astronomical Society

    23 publications · 1.3K citations

    18

    h-index

  5. Biometrics

    19 publications · 834 citations

    14

    h-index

1–5