The day started very early with the Gertrude Cox Scholarship 5k race, since my wife and I had to leave the hotel at 5:15am to catch the first metro to the RFK stadium. We met other runners in the metro and we all managed to get to the parking lot of the stadium. There were actually fewer runners than at the previous Gertrude Cox races I ran (like the first one in 1989 in D.C.), maybe around 40 of us, and the track for the race was one loop around the huge parking lot, not inside the stadium quite obviously. We started at about 6:20am in a warm humid weather and I managed to keep track with the two leaders for about one kilometer (3:38) before setting to my own pace. I stuck to a third place for the rest of the race, ending up in 18:28 about 30 seconds behind David Dunson and more than a minute behind the winner, in what felt like more than 5k.
The first session I attended was the Medallion lecture by Allistair Sinclair who talked about exact convergence speeds for MCMC algorithms in combinatorics. While the talk was beautifully organised and quite broad in reaching to the audience, I must admit I ended up being disappointed at the lack of connection with the MCMC developments found in Statistics, especially the huge corpus of work by Gareth Roberts and Jeff Rosenthal. This is another illustration of the gap between computer scientists working in combinatorics and applied probabilists, even though they are using the same tools. In the afternoon, I went to the Savage Award Finalists session, where the four finalist were presenting their PhD thesis work. Interestingly, they all have some Bayesian features in their work, albeit from different perspectives, and David Dunson managed to give a great discussion on those four theses at the same pace he ran the morning 5k! Later that day, at the SBSS (Section on Bayesian Statistical Science) mixer, the Savage Award was given to Lorenzo Trippa from Milano, now at the M.D. Anderson Cancer Center, Texas A & M, for his extensions of Polya tree models.
I was mentioning the new books in the Use R! series in the previous post. I spotted yesterday a book by Phil Spector on Data Manipulation with R that I immediately bought because Phil’s material on R available on the web has been quite helpful in writing Introducing Monte Carlo Methods with R. (Hence the free cap!) Note that he should not be confused with the music producer Phil Spector, who worked with the Ramones and is now in jail! I incidentally spotted two copies of the paperback version of the The Bayesian Choice
printed in hard-cover by mistake but sold at the paperback price. (This is due to the new print-on-demand strategy of publishers that eliminates inventory.)
