Information Criterion Model Selection

Information Criterion Model Selection is a model selection method in phylogenetics that uses information-theoretic criteria, such as the Akaike or Bayesian Information Criterion, to balance model fit and complexity by penalizing the number of parameters to avoid overfitting.

715

Publications

90.3K

Citations

2.2K

Authors

985

Institutions

Publications per year

2017–2026

136

Authors

2.2K

  1. GC
    Gerda Claeskens

    KU Leuven, Belgium

    13 publications · 915 citations

    12

    h-index

  2. CT
    Chih‐Ling Tsai

    University of California, Davis, United States

    8 publications · 1.3K citations

    8

    h-index

  3. JE
    Joseph E. Cavanaugh

    University of Iowa, United States

    7 publications · 1.2K citations

    7

    h-index

  4. GC
    Gary C. White

    Colorado State University, United States

    7 publications · 1.2K citations

    7

    h-index

  5. RL
    Runze Li

    Pennsylvania State University, United States

    6 publications · 168 citations

    6

    h-index

1–5 of 2.2K

Venues

  1. Journal of Wildlife Management

    35 publications · 8K citations

    26

    h-index

  2. 14

    h-index

  3. PLoS ONE

    13 publications · 1.1K citations

    13

    h-index

  4. Biometrics

    13 publications · 4.8K citations

    13

    h-index

  5. Biometrika

    12 publications · 3.4K citations

    12

    h-index

1–5