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.
|Number of pages||25|
|Journal||Annual Review of Statistics and Its Application|
|Early online date||28 Nov 2018|
|Publication status||Published - 7 Mar 2019|
- intractable likelihood
- Monte Carlo