Bayesian Model Criticism

Bayesian Model Criticism is a methodological framework within Bayesian statistics that evaluates the adequacy and assumptions of a Bayesian model by assessing the consistency between the model's posterior predictions and the observed data, often through posterior predictive checks, residual analysis, or sensitivity diagnostics.

39

Publications

11K

Citations

70

Authors

42

Institutions

Publications per year

2017–2026

2

Authors

70

  1. DJ
    David J. Spiegelhalter

    MRC Biostatistics Unit, United Kingdom

    4 publications · 2K citations

    4

    h-index

  2. SR
    Sylvia Richardson

    Imperial College London, United Kingdom

    3 publications · 222 citations

    3

    h-index

  3. PJ
    P. J. Harrison

    University of Warwick, United Kingdom

    2 publications · 606 citations

    2

    h-index

  4. AL
    Andrew L. Rukhin

    National Institute of Standards and Technology, United States

    2 publications · 472 citations

    2

    h-index

  5. JG
    Jørund Gåsemyr

    University of Oslo, Norway

    2 publications · 39 citations

    2

    h-index

1–5 of 70

Venues

  1. Bayesian Analysis

    6 publications · 168 citations

    6

    h-index

  2. Scandinavian Journal of Statistics

    3 publications · 67 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 249 citations

    3

    h-index

  4. 3

    h-index

  5. Technometrics

    3 publications · 2.6K citations

    3

    h-index

1–5