Model Adequacy

Model Adequacy is the extent to which a statistical model sufficiently captures the underlying structure and patterns of observed data, as evaluated through Bayesian posterior predictive checks and comparative assessment against alternative models.

289

Publications

32.4K

Citations

642

Authors

330

Institutions

Publications per year

2017–2026

59

Authors

642

  1. SD
    Sebastián Duchêne

    The University of Melbourne, Australia

    5 publications · 196 citations

    5

    h-index

  2. DA
    David A. Duchêne

    The University of Sydney, Australia

    4 publications · 159 citations

    4

    h-index

  3. AS
    Aris Spanos

    Virginia Tech, United States

    3 publications · 154 citations

    3

    h-index

  4. SL
    Shiqing Ling

    Hong Kong University of Science and Technology, Hong Kong SAR China

    3 publications · 334 citations

    3

    h-index

  5. KL
    Kjetil Lysne Voje

    University of Oslo, Norway

    3 publications · 86 citations

    3

    h-index

1–5 of 642

Venues

  1. Journal of the American Statistical Association

    12 publications · 6.4K citations

    12

    h-index

  2. Technometrics

    9 publications · 779 citations

    9

    h-index

  3. Biometrics

    7 publications · 1.4K citations

    7

    h-index

  4. Water Resources Research

    6 publications · 1.3K citations

    6

    h-index

  5. Statistics in Medicine

    5 publications · 182 citations

    5

    h-index

1–5