Deviance Information Criteria for Model Selection in Approximate Bayesian Computation

@article{Franois2011DevianceIC,
  title={Deviance Information Criteria for Model Selection in Approximate Bayesian Computation},
  author={Olivier François and Guillaume Laval},
  journal={Statistical Applications in Genetics and Molecular Biology},
  year={2011},
  volume={10}
}
  • O. FrançoisG. Laval
  • Published 2 May 2011
  • Biology
  • Statistical Applications in Genetics and Molecular Biology
Approximate Bayesian computation (ABC) is a class of algorithmic methods in Bayesian inference using statistical summaries and computer simulations. ABC has become popular in evolutionary genetics and in other branches of biology. However, model selection under ABC algorithms has been a subject of intense debate during the recent years. Here, we propose novel approaches to model selection based on posterior predictive distributions and approximations of the deviance. We argue that this… 

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