Overview of Approximate Bayesian Computation
S. A. Sisson, Y. Fan, M. A. Beaumont
TL;DR
This chapter provides a comprehensive overview of Approximate Bayesian Computation (ABC), explaining its core ideas, concepts, and applications through numerous examples and illustrations.
Contribution
It offers a detailed introduction to ABC methods, clarifying their principles and practical use, serving as a foundational resource for researchers.
Findings
Clarifies core ABC concepts
Provides numerous practical examples
Serves as an introductory guide
Abstract
This Chapter, "Overview of Approximate Bayesian Computation", is to appear as the first chapter in the forthcoming Handbook of Approximate Bayesian Computation (2018). It details the main ideas and concepts behind ABC methods with many examples and illustrations.
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Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Quantum chaos and dynamical systems · Stochastic processes and statistical mechanics