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Approximate Bayesian Computation
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DOI：10.1146/annurev-statistics-030718-105212.png)
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摘要
En 中文
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.
Keyword:
Monte Carlo
intractable likelihood
Bayesian
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期刊
IF:
8.7
论文数:
211
被引数:
2.4K
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