ABC Samplers
arXiv:1802.09650v129 citations
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It provides a reference for researchers in Bayesian statistics, but it is incremental as it summarizes known methods without new results.
The chapter reviews existing algorithms for sampling from approximate Bayesian computation (ABC) posteriors, including rejection/importance sampling, MCMC, and sequential Monte Carlo methods, as part of a handbook compilation.
This Chapter, "ABC Samplers", is to appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). It details the main ideas and algorithms used to sample from the ABC approximation to the posterior distribution, including methods based on rejection/importance sampling, MCMC and sequential Monte Carlo.