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
715
1–5 of 715
2.2K
12
h-index
8
h-index
7
h-index
7
h-index
6
h-index
1–5 of 2.2K
985
University of California, Berkeley
Berkeley, United States
13 h-index
19 publications
2.1K citations
United States Geological Survey
Reston, United States
12 h-index
22 publications
1.1K citations

Centre National de la Recherche Scientifique
Paris, France
11 h-index
21 publications
1.9K citations
University of California, Davis
Davis, United States
11 h-index
14 publications
2.9K citations
Colorado State University
Fort Collins, United States
10 h-index
14 publications
14.1K citations
KU Leuven
Leuven, Belgium
10 h-index
20 publications
839 citations
The University of Tokyo
Tokyo, Japan
10 h-index
20 publications
1.3K citations

University of British Columbia
Vancouver, Canada
9 h-index
30 publications
3.9K citations
1–8 of 985
35 publications · 8K citations
26
h-index
14 publications · 8K citations
14
h-index
13 publications · 1.1K citations
13
h-index
13 publications · 4.8K citations
13
h-index
12 publications · 3.4K citations
12
h-index
1–5