Approximate Bayesian Computation
Likelihood-free inference and simulation-based methods.
Approximate Bayesian Computation. Likelihood-free inference and simulation-based methods.
Foundations and canonical references
The standard treatments of approximate bayesian computation approach the subject from complementary angles. Sisson, Handbook of Approximate Bayesian Computation (2018) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to.
Open methodological questions for approximate bayesian computation include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 2018Handbook of Approximate Bayesian Computationsisson-2018, fan-2018, beaumont-2018
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