• Home
• Staff & Students
• Vacancies

Christian Robert

 

 

http://www.ceremade.dauphine.fr/~xian/

 

Wednesday 6th February 2013

Time: 4pm

 

Basement Seminar Room

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

 

Approximate Bayesian Computation (ABC) as a new empirical Bayes approach

 

 

 

Approximate Bayesian computation (ABC) has now become an essential tool for the analysis of complex stochastic models when the likelihood function is unavailable. The well-established statistical method of empirical likelihood however provides another route to such settings that bypasses simulations from the model and the choices of the ABC parameters (summary statistics, distance, tolerance), while being provably convergent in the number of observations. Furthermore, avoiding model simulations leads to significant time savings in complex models, as those used in population genetics. The ABCel algorithm we present in this talk provides in addition an evaluation of its own performances through an associated effective sample size.
The method is illustrated on several realistic examples. (Joint work with K.L. Mengersen and P. Pudlo)