Deviance Information Criterion

Deviance Information Criterion is a Bayesian model comparison metric that belongs to the class of information criteria by combining a measure of model fit based on the posterior deviance with a penalty for model complexity measured by the effective number of parameters.

284

Publications

30.9K

Citations

793

Authors

445

Institutions

Publications per year

2017–2026

73

Authors

793

  1. MC
    Ming‐Hui Chen

    University of Connecticut, United States

    5 publications · 79 citations

    5

    h-index

  2. LV
    L. Varona

    Universidad de Zaragoza, Spain

    5 publications · 227 citations

    5

    h-index

  3. AE
    A. E. Ades

    University of Bristol, United Kingdom

    5 publications · 328 citations

    5

    h-index

  4. JC
    J. Casellas

    Universitat Autònoma de Barcelona, Spain

    5 publications · 207 citations

    5

    h-index

  5. JY
    Jun Yu

    Singapore Management University, Singapore

    5 publications · 426 citations

    5

    h-index

1–5 of 793

Venues

  1. Statistics in Medicine

    17 publications · 714 citations

    14

    h-index

  2. PLoS ONE

    9 publications · 416 citations

    9

    h-index

  3. Journal of Animal Science

    7 publications · 490 citations

    7

    h-index

  4. Biometrics

    7 publications · 771 citations

    7

    h-index

  5. Journal of Wildlife Management

    5 publications · 3.8K citations

    5

    h-index

1–5