An introduction to Bayesian synthetic likelihood
Date: 27 October 2020, Tuesday
Time: 11am AEDT
Speaker: Dr Leah South (Queensland University of Technology)
Abstract:
Many complex statistical models have intractable likelihoods, making standard methods for estimating the posterior distribution that use direct likelihood evaluation infeasible. In these contexts, the benefits of likelihood-free methods such as Bayesian synthetic likelihood (BSL) become apparent. Instead of evaluating the likelihood, BSL approximates the likelihood of a judiciously chosen summary statistic of the data via model simulation and density estimation. Relative to its competitor approximate Bayesian computation (ABC), BSL requires little tuning and less model simulations when the chosen summary statistic is high-dimensional. This talk will introduce the BSL method, several recent extensions and our R associated software.
This is joint work with Chris Drovandi, Ziwen An, David Nott and Anthony Lee.
The seminar is hosted by University of Technology Sydney.
Link: https://zoom.uts.edu.au/j/84070979066
Password: BayesStats
Date: 27 October 2020, Tuesday
Time: 11am AEDT
Speaker: Dr Leah South (Queensland University of Technology)
Abstract:
Many complex statistical models have intractable likelihoods, making standard methods for estimating the posterior distribution that use direct likelihood evaluation infeasible. In these contexts, the benefits of likelihood-free methods such as Bayesian synthetic likelihood (BSL) become apparent. Instead of evaluating the likelihood, BSL approximates the likelihood of a judiciously chosen summary statistic of the data via model simulation and density estimation. Relative to its competitor approximate Bayesian computation (ABC), BSL requires little tuning and less model simulations when the chosen summary statistic is high-dimensional. This talk will introduce the BSL method, several recent extensions and our R associated software.
This is joint work with Chris Drovandi, Ziwen An, David Nott and Anthony Lee.
The seminar is hosted by University of Technology Sydney.
Link: https://zoom.uts.edu.au/j/84070979066
Password: BayesStats