Recent developments allow Bayesian analysis also when the likelihood function is intractable, that means it is analytically unavailable or computationally prohibitive to evaluate. These methods are known as “approximate Bayesian computation” (ABC) or likelihood-free methods and are characterized by the fact that the approximation of the posterior distribution is obtained without explicitly evaluating the likelihood function. This kind of analysis is popular in genetic and financial settings. In this work, ABC and some possible applications will be presented.
Approximate Bayesian computation and applications / Grazian, Clara. - ELETTRONICO. - (2013). (Intervento presentato al convegno Complez Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction, S.Co. 2013 tenutosi a Milano nel 9-11/09/2013).
Approximate Bayesian computation and applications
GRAZIAN, CLARA
2013
Abstract
Recent developments allow Bayesian analysis also when the likelihood function is intractable, that means it is analytically unavailable or computationally prohibitive to evaluate. These methods are known as “approximate Bayesian computation” (ABC) or likelihood-free methods and are characterized by the fact that the approximation of the posterior distribution is obtained without explicitly evaluating the likelihood function. This kind of analysis is popular in genetic and financial settings. In this work, ABC and some possible applications will be presented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
