Another great day of talks and discussions at BIRS! Continuing on the themes of the workshop between delving into the further validation of those approximation techniques and the devising of ever more approximate solutions for ever more complex problems. Among the points that came clearer to me through discussion, a realisation that the synthetic likelihood perspective is not that far away from our assumptions in the consistency paper. And that a logistic version of the approach can be constructed as well. A notion I had not met before (or have forgotten I had met) is the one of early rejection ABC, which should actually be investigated more thoroughly as it should bring considerable improvement in computing time (with the caveats of calibrating the acceptance step before producing the learning sample and of characterising the output). Both Jukka Corander and Ewan Cameron reminded us of the case of models that take minutes or hours to produce one single dataset. (In his talk on some challenging applications, Jukka Corander chose to move from socks to boots!) And Jean-Michel Marin produced an illuminating if sobering experiment on the lack of proper Bayesian coverage by ABC solutions. (It appears that Ewan’s video includes a long empty moment when we went out for the traditional group photo, missing the end of his talk.)
Archive for ABC convergence
Today, I fly from Paris to Amsterdam to Calgary to attend the ABC’ory workshop (15w2214) at the Banff International Research Station (BIRS) that Luke Bornn, Jukka Corander, Gael Martin, Dennis Prangle, Richard Wilkinson and myself built. The meeting is to brainstorm about the foundations of ABC for statistical inference rather than about the computational aspects of ABC, but the schedule is quite flexible for other directions!
Since I could not download the slides of my ABC course in Les Diablerets in one go, I broke them by chapters as follows. (Warning: there is very little novelty in those slides, except for the final part on consistency.)
Although I did not do it on purpose (!), starting with indirect inference and other methods inspired from econometrics induced some discussion in the first hour of the course with econometricians in the room. Including Elvezio Ronchetti.
I also regretted piling too much material in the alphabet soup, as it was too widespread for a new audience. And as I could not keep the coherence of the earlier parts by going thru so many papers at once. Especially since I was a bit knackered after a day of skiing….
I managed to get to the final convergence chapter on the last day, even though I had to skip some of the earlier material. Which should be reorganised anyway as the parts between model choice with random forests and inference with random forests are not fully connected!
Taking advantage of being in San Francisco, I flew yesterday to Australia over the Pacific, crossing for the first time the day line. The 15 hour Qantas flight to Sydney was remarkably smooth and quiet, with most passengers sleeping for most of the way, and it gave me a great opportunity to go over several papers I wanted to read and review. Over the next week or so, I will work with my friends and co-authors David Frazier and Gael Martin at Monash University (and undoubtedly enjoy the great food and wine scene!). Before flying back to Paris (alas via San Francisco rather than direct).