Model Selection and Model Averaging in Phylogenetics: Advantages of Akaike Information Criterion and Bayesian Approaches Over Likelihood Ratio Tests
Universidade de Vigo · Manaaki Whenua – Landcare Research
Abstract
Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods…
Citation impact
- FWCI
- 61.47
- Percentile
- 100%
- References
- 197
Authors
2Topics & keywords
- Akaike information criterion
- Bayesian information criterion
- Model selection
- Bayesian inference
- Selection (genetic algorithm)
- Inference
- Likelihood-ratio test
- Bayesian probability