Hierarchical Bayesian Model

A Hierarchical Bayesian Model is a probabilistic model that belongs to the class of Bayesian statistical models and is distinguished by its incorporation of multiple levels of parameters, wherein higher-level parameters govern the distribution of lower-level parameters, thereby enabling the modeling of complex dependencies and uncertainty propagation through conditional probability specifications across hierarchical layers.

2.9K

Publications

209.7K

Citations

11.5K

Authors

2.8K

Institutions

Publications per year

2017–2026

1.1K

Variants

Hierarchical Bayesian ModelsMultilevel Bayesian ModelMultilevel Bayesian Models

Authors

11.5K

  1. BP
    Bradley P. Carlin

    University of Minnesota, United States

    22 publications · 2.4K citations

    19

    h-index

  2. SR
    Sylvia Richardson

    Imperial College London, United Kingdom

    17 publications · 4.3K citations

    17

    h-index

  3. ME
    Majid Ezzati

    Imperial College London, United Kingdom

    14 publications · 20K citations

    14

    h-index

  4. MP
    Martin Pelikán

    University of Illinois Urbana-Champaign, United States

    15 publications · 846 citations

    13

    h-index

  5. KΕ
    Klaas Ε. Stephan

    University College London, United Kingdom

    13 publications · 1.5K citations

    12

    h-index

1–5 of 11.5K

Venues

  1. Journal of the American Statistical Association

    84 publications · 6.5K citations

    40

    h-index

  2. Statistics in Medicine

    70 publications · 6.1K citations

    30

    h-index

  3. Monthly Notices of the Royal Astronomical Society

    45 publications · 1.9K citations

    27

    h-index

  4. PLoS ONE

    50 publications · 2.2K citations

    27

    h-index

  5. arXiv (Cornell University)

    Repository · 47 publications · 3.1K citations

    24

    h-index

1–5