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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Robert, Christian P. Pillai, Natesh S. Marin, Jean-michel Cornuet, Jean-marie |
| Description | Author Affiliation: Robert CP ( Université Paris-Dauphine, 75775 Paris cedex 16, France. Christian.Robert@ceremade.dauphine.fr); |
| Abstract | Approximate Bayesian computation (ABC) have become an essential tool for the analysis of complex stochastic models. Grelaud et al. [(2009) Bayesian Anal 3:427-442] advocated the use of ABC for model choice in the specific case of Gibbs random fields, relying on an intermodel sufficiency property to show that the approximation was legitimate. We implemented ABC model choice in a wide range of phylogenetic models in the Do It Yourself-ABC (DIY-ABC) software [Cornuet et al. (2008) Bioinformatics 24:2713-2719]. We now present arguments as to why the theoretical arguments for ABC model choice are missing, because the algorithm involves an unknown loss of information induced by the use of insufficient summary statistics. The approximation error of the posterior probabilities of the models under comparison may thus be unrelated with the computational effort spent in running an ABC algorithm. We then conclude that additional empirical verifications of the performances of the ABC procedure as those available in DIY-ABC are necessary to conduct model choice. |
| ISSN | 00278424 |
| e-ISSN | 10916490 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number | 37 |
| Volume Number | 108 |
| Language | English |
| Publisher | National Academy of Sciences |
| Publisher Date | 2011-09-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Bayes Theorem Computational Biology Computer Simulation Genetics, Population Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Multidisciplinary |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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