SMS scnews item created by Munir Hiabu at Tue 27 Oct 2020 0939
Type: Seminar
Distribution: World
Expiry: 27 Oct 2020
Calendar1: 27 Oct 2020 1100-1200
CalLoc1: https://zoom.uts.edu.au/j/84070979066
CalTitle1: An introduction to Bayesian synthetic likelihood
Auth: munir@119-18-1-53.771201.syd.nbn.aussiebb.net (mhia8050) in SMS-WASM

Statistics Across Campuses: Leah South -- An introduction to Bayesian synthetic likelihood

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


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