Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo.

  title={Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo.},
  author={John P. Huelsenbeck and Bret Larget and Michael E. Alfaro},
  journal={Molecular biology and evolution},
  volume={21 6},
A common problem in molecular phylogenetics is choosing a model of DNA substitution that does a good job of explaining the DNA sequence alignment without introducing superfluous parameters. A number of methods have been used to choose among a small set of candidate substitution models, such as the likelihood ratio test, the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and Bayes factors. Current implementations of any of these criteria suffer from the limitation… CONTINUE READING
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