Back from Philly

[This article was first published on Xi'an's Og » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The conference in honour of Larry Brown was quite exciting, with lots of old friends gathered in Philadelphia and lots of great talks either recollecting major works of Larry and coauthors or presenting fairly interesting new works. Unsurprisingly, a large chunk of the talks was about admissibility and minimaxity, with John Hartigan starting the day re-reading Larry masterpiece 1971 paper linking admissibility and recurrence of associated processes, a paper I always had trouble studying because of both its depth and its breadth! Bill Strawderman presented a new if classical minimaxity result on matrix estimation and Anirban DasGupta some large dimension consistency results where the choice of the distance (total variation versus Kullback deviance) was irrelevant. Ed George and Susie Bayarri both presented their recent work on g-priors and their generalisation, which directly relate to our recent paper on that topic. On the afternoon, Holger Dette showed some impressive mathematics based on Elfving’s representation and used in building optimal designs. I particularly appreciated the results of a joint work with Larry presented by Robert Wolpert where they classified all Markov stationary infinitely divisible time-reversible integer-valued processes. It produced a surprisingly small list of four cases, two being trivial.. The final talk of the day was about homology, which sounded a priori rebutting, but Robert Adler made it extremely entertaining, so much that I even failed to resent the powerpoint tricks! The next morning, Mark Low gave a very emotional but also quite illuminating about the first results he got during his PhD thesis at Cornell (completing the thesis when I was using Larry’s office!). Brenda McGibbon went back to the three truncated Poisson papers she wrote with Ian Johnstone (via gruesome 13 hour bus rides from Montréal to Ithaca!) and produced an illuminating explanation of the maths at work for moving from the Gaussian to the Poisson case in a most pedagogical and enjoyable fashion. Larry Wasserman explained the concepts at work behind the lasso for graphs, entertaining us with witty acronyms on the side!, and leaving out about 3/4 of his slides! (The research group involved in this project produced an R package called huge.) Joe Eaton ended up the morning with a very interesting result showing that using the right Haar measure as a prior leads to a matching prior, then showing why the consequences of the result are limited by invariance itself. Unfortunately, it was then time for me to leave and I will miss (in both meanings of the term) the other half of the talks. Especially missing Steve Fienberg’s talk for the third time in three weeks! Again, what I appreciated most during those two days (besides the fact that we were all reunited on the very day of Larry’s birthday!) was the pain most speakers went to to expose older results in a most synthetic and intuitive manner… I also got new ideas about generalising our parallel computing paper for random walk Metropolis-Hastings algorithms and for optimising across permutation transforms.


Filed under: R, Statistics, Travel, University life Tagged: admissibility, graphs, homotopy, invariance, Larry Brown, Lasso, minimaxity, non-pa, Philadelp, Wharton Business School

To leave a comment for the author, please follow the link and comment on their blog: Xi'an's Og » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)