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Approximate Bayesian Computation
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OA
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DOI：10.1146/annurev-statistics-030718-105212.png)
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Abstract
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Many of the statistical models that could provide an accurate, interesting, and testable explanation for the structure of a data set turn out to have intractable likelihood functions. The method of approximate Bayesian computation (ABC) has become a popular approach for tackling such models. This review gives an overview of the method and the main issues and challenges that are the subject of current research.
Keywords:
Monte Carlo
intractable likelihood
Bayesian
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