One World ABC Seminar: Hien Duy Nguyen

on the June 18, 2020

at 11:30 am [UK time]
For this sixth session of the One World ABC Seminar, Hien Duy Nguyen from La Trobe University will talk about "Approximate Bayesian computation via the energy statistic".

Inspired by the "One World Probability Seminar", we decided to run The One World ABC Seminar, a weekly/fortnightly series of seminars that will take place on Blackboard Collaborate on Thursdays at 11.30am [UK time]. The idea is to gather members and disseminate results and innovation during these weeks and months under lockdown.

Hien Duy Nguyen

Approximate Bayesian computaiton (ABC) has become an essential part of the Bayesian toolbox, for addressing problems in which the likelihood function is prohibitively expensive to compute, or when it is entirely unknown. ABC defines a pseudo-posterior distribution by comparing observed data with simulated data, traditionally using some summary statistic, which may be difficult to elicit. Recently, data discrepancy measures have been proposed in order to bypass the problem of constructing summary statistics. In this talk, we follow this approach and propose an ABC algorithm using the so-called two-sample energy statistic.
Using the energy statistic as our data discrepancy measurement, we establish various theoretical results such as convergence of the posterior distribution as the sample size becomes large and as the rejection threshold becomes small. Application of our approach is demonstrated on a variety of models and compared against some alternative discrepancy measurement-based methods.
This is joint work with Julyan Arbel, Hongliang Lü, and Florence Forbes (Inria, Grenoble Rhône-Alpes).
Published on June 5, 2020