Approximate Bayesian Computation (ABC) is a likelihood‐free inference methodology that has revolutionised the way researchers tackle complex problems where the likelihood function is difficult or ...

ABC (approximate Bayesian computation) is a general approach for dealing with models with an intractable likelihood. In this work, we derive ABC algorithms based on QMC (quasi-Monte Carlo) sequences.

Over the past ten years, Approximate Bayesian Computation (ABC) has become hugely popular to estimate the parameters of a model when the likelihood function cannot be computed in a reasonable amount ...

Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and ...