A new day at JSM 2011, admittedly not as tense as Monday, but still full. After a long run in the early hours when I took this picture, I started the day with the Controversies in the philosophy of Bayesian statistics with Jim Berger and Andrew Gelman, Rob Kass and Cosma Shalizi being unable to make it. From my point of view it was a fun session, even though I wish I had been more incisive! But I agreed with most of Jim said, so… It is too bad we could not cover his last point about the Bayesian procedures that were not Bayesianly justified (like posterior predictives) as I was quite interested in the potential discussion in this matter (incl. the position of the room on ABC!). Anyway, I am quite thankful to Andrew for setting up this session.As Jum said, we should have those more often, especially when the attendance was large enough to fill a double room at 8:30am.
Incidentally, I managed to have a glaring typo in my slides, pointed out by Susie Bayarri: Bayes theorem was written as
Aie, aie, aie! Short of better scapegoats, I will blame the AF plane for this… (This was a good way to start a controversy, however no one raised to the bait!) A more serious question reminded me of the debate surrounding A Search for Certainty: It was whether frequentist and subjective Bayes approaches had more justifications than the objective Bayes approach, in the light of von Mises‘ and personalistic (read, de Finetti) interpretations of probability.
While there were many possible alternatives for the next session, I went to attend Sylvia Richardson’s Medallion Lecture. This made sense on many levels, the primary one being that Sylvia and I worked and are working on rather close topics, from mixtures of distributions, to variable selection, to ABC. So I was looking forward the global picture she would provide on those topics. I particularly enjoyed the way she linked mixtures with more general modelling structures, through extensions in the distribution of the latent variables. (This is also why I am attending Chris Holmes’ Memorial Lecture tomorrow, with the exciting title of Loss, Actions, Decisions: Bayesian Analysis in High-Throughput Genomics.)
In the afternoon, I only attended one talk by David Nott, Efficient MCMC Schemes for Computationally Expensive Posterior Distribution, which involved hybrid Monte Carlo on complex likelihoods. This was quite interesting, as hybrid Monte Carlo is indeed the solution to diminish the number of likelihood evaluations, since it moves along iso-density slices… After this, we went working on ABC model choice with Jean-Michel Marin and Natesh Pillai. Before joining the fun at the Section for Bayesian statistical mixer, where the Savage and Mitchell and student awards were presented. This was the opportunity to see friends, meet new Bayesians, and congratulate the winners, including Julien Cornebise and Robin Ryder of course.