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abc: an R package for approximate Bayesian computation (ABC)
Article first published online: 31 JAN 2012
© 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society
Methods in Ecology and Evolution
Volume 3, Issue 3, pages 475–479, June 2012
How to Cite
Csilléry, K., François, O. and Blum, M. G. B. (2012), abc: an R package for approximate Bayesian computation (ABC). Methods in Ecology and Evolution, 3: 475–479. doi: 10.1111/j.2041-210X.2011.00179.x
- Issue published online: 7 JUN 2012
- Article first published online: 31 JAN 2012
- Received 4 September 2011; accepted 22 November 2011 Handling Editor: Robert Freckleton
- model-based inference;
- neural networks;
- population genetics
1. Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data. Approximate Bayesian computation (ABC) is devoted to these complex models because it bypasses the evaluation of the likelihood function by comparing observed and simulated data.
2. We introduce the R package ‘abc’ that implements several ABC algorithms for performing parameter estimation and model selection. In particular, the recently developed nonlinear heteroscedastic regression methods for ABC are implemented. The ‘abc’ package also includes a cross-validation tool for measuring the accuracy of ABC estimates and to calculate the misclassification probabilities when performing model selection. The main functions are accompanied by appropriate summary and plotting tools.
3. R is already widely used in bioinformatics and several fields of biology. The R package ‘abc’ will make the ABC algorithms available to a large number of R users. ‘abc’ is a freely available R package under the GPL license, and it can be downloaded at http://cran.r-project.org/web/packages/abc/index.html.