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2017

Multilevel Monte Carlo in Approximate Bayesian Computation

Jasra, Ajay, Jo, Seongil, Nott, David et al.

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In the following article we consider approximate Bayesian computation (ABC) inference.

We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC).
A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d.
sampling from the most accurate ABC approximation.

Multilevel Monte Carlo in Approximate Bayesian Computation · Around

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