abc: an R package for approximate Bayesian computation (ABC)

Summary 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…

• AN
  Agence Nationale de la Recherche