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Approximate Bayesian Computation

Approximate Bayesian Computation (ABC) is a family of simulation-based inference methods that estimate posterior distributions without requiring an analytically tractable likelihood function. Introduced by Beaumont, Zhang and Balding (2002) in the context of population genetics, ABC replaced the intractable likelihood with repeated model simulation and a comparison of summary statistics between simulated and observed data.

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Approximate Bayesian Computation (ABC)

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Same method familyApproximate Bayesian Computationmachine-suggested · Relational suggestion, not evidence.See alsoBayesian Inferencemachine-suggested · Relational suggestion, not evidence.Same method familyMarkov Chain Monte Carlomachine-suggested · Relational suggestion, not evidence.See alsoMONTE-CARLO-SIMULATIONmachine-suggested · Relational suggestion, not evidence.See alsoSequential Monte Carlomachine-suggested · Relational suggestion, not evidence.