Approximate Bayesian Computation : a non-parametric perspective

  title={Approximate Bayesian Computation : a non-parametric perspective},
  author={Michael G. B. Blum},
Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics sobs from the data and simulating summary statistics for different values of the parameter . The posterior distribution is then approximated by an estimator of the conditional density g( |sobs). In this paper, we derive the asymptotic bias… CONTINUE READING
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