A Note on Target Distribution Ambiguity for Likelihood-Free Samplers (ABC)

Scott Sisson, Gareth Peters, Mark Briers, Yanan Fan

Research output: Working paper

Abstract

Methods for Bayesian simulation in the presence of computationally intractable likelihood functions are of growing interest. Termed likelihood-free samplers, standard simulation algorithms such as Markov chain Monte Carlo have been adapted for this setting. In this article, by presenting generalisations of existing algorithms, we demonstrate that likelihood-free samplers can be ambiguous over the form of the target distribution. We also consider the theoretical justification of these samplers. Distinguishing between the forms of the target distribution may have implications for the future development of likelihood-free samplers.
Original languageEnglish
PublisherarXiv
Publication statusPublished - 28 May 2010

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