EasyABC: performing efficient approximate Bayesian computation sampling schemes using R
Article first published online: 8 APR 2013
© 2013 The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society
Methods in Ecology and Evolution
Volume 4, Issue 7, pages 684–687, July 2013
How to Cite
Jabot, F., Faure, T., Dumoulin, N. (2013), EasyABC: performing efficient approximate Bayesian computation sampling schemes using R. Methods in Ecology and Evolution, 4: 684–687. doi: 10.1111/2041-210X.12050
- Issue published online: 2 JUL 2013
- Article first published online: 8 APR 2013
- Accepted manuscript online: 11 MAR 2013 03:26AM EST
- Manuscript Accepted: 4 MAR 2013
- Manuscript Received: 30 JAN 2013
- Irstea project DynIndic
- French National Research Agency (ANR)
- SYSCOMM project DISCO. Grant Number: ANR-09-SYSC-003
- Approximate Bayesian computation;
- Markov chain Monte Carlo;
- model selection;
- model-based inference;
- parameter estimation;
- sequential Monte Carlo
- Approximate Bayesian computation (ABC), a type of likelihood-free inference, is a family of statistical techniques to perform parameter estimation and model selection. It is increasingly used in ecology and evolution, where the models used can be too complex to be handled with standard likelihood techniques. The essence of ABC techniques is to compare simulation outputs to observed data, in order to select the parameter values of the simulations which best fit the data. ABC techniques are thus computationally demanding. This constitutes a key limitation to their implementation.
- We introduce the R package ‘EasyABC’ that enables one to launch a series of simulations from the R platform and to retrieve the simulation outputs in an appropriate format for post-processing. The ‘EasyABC’ package further implements several efficient parameter sampling schemes to speed up the ABC procedure: on top of the standard prior sampling, it implements various algorithms to perform sequential (ABC-sequential) and Markov chain Monte Carlo (ABC-MCMC) sampling schemes. The package functions can furthermore make use of parallel computing.
- The R package ‘EasyABC’ complements the package ‘abc’ which enables various post-processing of simulation outputs. ‘EasyABC’ makes several state-of-the-art ABC implementations available to the large community of R users in the fields of ecology and evolution. It is a freely available R package under the GPL license, and it can be downloaded at http://cran.r-project.org/web/packages/EasyABC/index.html.