Korean trip

A fairly short but exciting trip to Seoul and to the Fall meeting of the Korean Statistical Society there. Plus giving a seminar at Seoul National University, where I stayed and enjoyed its beautiful campus surrounded by hills painted in the flamboyant reds and yellows of trees. Running to the top of Gwanaksan in the early morning, with some scrambling moments, was a fantastic beginning for the day! Although it was quite unintentional Sacha Tsybakov from CREST happened to be another invited speaker at the meeting (along with Regina Liu from Rutgers, whom I was also met in Salzburg two months ago) and we had a nice stroll together on the University of Seoul campus during a break in the sessions, gaining another view of the city from the top of the Bukhasan mountain. The talk I gave there on the asymptotics of ABC happened to be more attended than my tutorial lecture delivered at the beginning of JSM in Denver this summer. I am thus quite grateful to the organisers for their invitation and this opportunity to meet Korean statisticians and to get a glimpse of Korean culture and cuisine!

 

snapshot from Warwick [jatp]

Harvard snow sprinkle

SPA 2015 Oxford

Today I gave a talk on Approximate Bayesian model choice via random forests at the yearly SPA (Stochastic Processes and their Applications) 2015 conference, taking place in Oxford (a nice town near Warwick) this year. In Keble College more precisely. The slides are below and while they are mostly repetitions of earlier slides, there is a not inconsequential novelty in the presentation, namely that I included our most recent and current perspective on ABC model choice. Indeed, when travelling to Montpellier two weeks ago, we realised that there was a way to solve our posterior probability conundrum!

Despite the heat wave that rolled all over France that week, we indeed figured out a way to estimate the posterior probability of the selected (MAP) model, way that we had deemed beyond our reach in previous versions of the talk and of the paper. The fact that we could not provide an estimate of this posterior probability and had to rely instead on a posterior expected loss was one of the arguments used by the PNAS reviewers in rejecting the paper. While the posterior expected loss remains a quantity worth approximating and reporting, the idea that stemmed from meeting together in Montpellier is that (i) the posterior probability of the MAP is actually related to another posterior loss, when conditioning on the observed summary statistics and (ii) this loss can be itself estimated via a random forest, since it is another function of the summary statistics. A posteriori, this sounds trivial but we had to have a new look at the problem to realise that using ABC samples was not the only way to produce an estimate of the posterior probability! (We are now working on the revision of the paper for resubmission within a few week… Hopefully before JSM!)