Bayesian Model Checking

Bayesian Model Checking is a model evaluation procedure within Bayesian data analysis that assesses the consistency between observed data and the predictions of a fitted Bayesian model by leveraging posterior predictive distributions to detect systematic discrepancies indicating potential model inadequacy.

199

Publications

11.8K

Citations

470

Authors

261

Institutions

Publications per year

2017–2026

48

Authors

470

  1. SS
    Sandip Sinharay

    Educational Testing Service, United States

    11 publications · 803 citations

    11

    h-index

  2. HS
    Hal S. Stern

    University of California, Irvine, United States

    4 publications · 466 citations

    4

    h-index

  3. AG
    Andrew Gelman

    Columbia University, United States

    4 publications · 243 citations

    4

    h-index

  4. IV
    Iven Van Mechelen

    KU Leuven, Belgium

    3 publications · 334 citations

    3

    h-index

  5. CJ
    Christopher J. Langmead

    Carnegie Mellon University, United States

    3 publications · 69 citations

    3

    h-index

1–5 of 470

Venues

  1. Physical review. D/Physical review. D.

    PRD · 5 publications · 147 citations

    5

    h-index

  2. Statistics in Medicine

    5 publications · 293 citations

    5

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 5 publications · 104 citations

    5

    h-index

  4. Journal of Statistical Planning and Inference

    5 publications · 225 citations

    5

    h-index

  5. 4

    h-index

1–5