Model Complexity Penalties

Model Complexity Penalties is a statistical framework in phylogenetic model selection that imposes constraints on model fit to prevent overparameterization by penalizing the inclusion of additional parameters, thereby favoring simpler models that achieve an optimal balance between goodness-of-fit and parsimony.

162

Publications

26.3K

Citations

462

Authors

228

Institutions

Publications per year

2017–2026

71

Authors

462

  1. SB
    Seungkwon Beack

    Electronics and Telecommunications Research Institute, South Korea

    3 publications · 79 citations

    3

    h-index

  2. MS
    Mi Suk Lee

    Kyung Hee University, South Korea

    3 publications · 79 citations

    3

    h-index

  3. KZ
    Kai Zhen

    Nankai University, China

    3 publications · 79 citations

    3

    h-index

  4. PM
    Pierre Moulin

    University of Illinois Urbana-Champaign, United States

    3 publications · 168 citations

    3

    h-index

  5. JS
    Jongmo Sung

    Electronics and Telecommunications Research Institute, South Korea

    3 publications · 79 citations

    3

    h-index

1–5 of 462

Venues

  1. arXiv (Cornell University)

    Repository · 14 publications · 1.1K citations

    12

    h-index

  2. The Annals of Statistics

    7 publications · 304 citations

    7

    h-index

  3. 4

    h-index

  4. The Journal of Experimental Education

    3 publications · 756 citations

    3

    h-index

  5. Analytical Chemistry

    3 publications · 89 citations

    3

    h-index

1–5