Journal article

Cross-validation to select Bayesian hierarchical models in phylogenetics

Sebastian Duchene, David A Duchene, Francesca Di Giallonardo, John-Sebastian Eden, Jemma L Geoghegan, Kathryn E Holt, Simon YW Ho, Edward C Holmes



BACKGROUND: Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validat..

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Awarded by NHMRC Australia Fellowship

Awarded by NHMRC of Australia

Awarded by National Health and Medical Research Council of Australia

Funding Acknowledgements

This research was funded by an NHMRC Australia Fellowship (AF30) awarded to E.C.H. S.Y.W.H. was supported by the Australian Research Council. KEH was supported by the NHMRC of Australia (Fellowship #1061409).