“those” coincidences

Last Thursday night, after a friendly dinner closing the ICMS workshop, I was rushing back to Pollock Halls to catch some sleep before a very early flight. When crossing North Bridge, on top of Waverley station, I then spotted in the crowd a well-known face of a fellow statistician from Cambridge University, on an academic visit to the University of Edinburgh that was completely unrelated with the workshop. Then, today, on my way back from submitting a visa request at the Indian embassy in Paris, I took the RER train for one stop between Gare du Nord and Chatelet. When I stood up from my seat and looked behind me, a senior (and most famous) mathematician was sitting right there, in deep conversation with a colleague about algorithms… Just two of “those” coincidences. (Edinburgh may be propitious to coincidences: at the last ICMS workshop I attended, I ended up in the same Indian restaurant as Marc Suchard, who also was on an academic visit to the University of Edinburgh that was completely unrelated with the workshop!)

Big Bayes stories in print [and in force]

The special issue of Statistical Science Kerrie Mengersen and I edited over the past three (four?) years is now out in print! Even though many ‘Og readers may have already seen the table of contents, here it is once again. We hope you will enjoy this 100 page long excursion in big Bayesiana. The papers are not freely accessible as “current papers” on the journal website but can yet be found in the “future papers” section. (If a sponsor wants to support turning the papers into open access version, he or she is most welcome to contact us or the IMS!) And, thanks to Larry for reminding me!, available on arXiv. Thanks to all authors, discussants, reviewers and special kudos to Jon Wellner for his constant help and support in putting the special issue together!

• Big Bayes Stories—Foreword Kerrie L. Mengersen and Christian P. Robert; 1
• Estimating the Distribution of Dietary Consumption Patterns Raymond J. Carroll; 2-8
• Estimation of HIV Burden through Bayesian Evidence Synthesis Daniela De Angelis, Anne M. Presanis, Stefano Conti and A. E. Ades; 9-17
• Bayesian Estimation of Population-Level Trends in Measures of Health Status Mariel M. Finucane, Christopher J. Paciorek, Goodarz Danaei and Majid Ezzati; 18-25
• How Bayesian Analysis Cracked the Red-State, Blue-State Problem Andrew Gelman; 26-35
• From Science to Management: Using Bayesian Networks to Learn about Lyngbya  Sandra Johnson, Eva Abal, Kathleen Ahern and Grant Hamilton; 36-41
• Experiences in Bayesian Inference in Baltic Salmon Management Sakari Kuikka, Jarno Vanhatalo, Henni Pulkkinen, Samu Mäntyniemi and Jukka Corander; 42-49
• Finding the Most Distant Quasars Using Bayesian Selection Methods Daniel Mortlock; 50-57
• Bayesian Population Projections for the United Nations Adrian E. Raftery, Leontine Alkema and Patrick Gerland; 58-68
• Search for the Wreckage of Air France Flight AF 447 Lawrence D. Stone, Colleen M. Keller, Thomas M. Kratzke and Johan P. Strumpfer; 69-80
• Galaxy Formation: Bayesian History Matching for the Observable Universe Ian Vernon, Michael Goldstein and Richard Bower; 81-90
• Discussion of Big Bayes Stories and BayesBag Peter Bühlmann; 91-94
• Discussion of “Estimating the Distribution of Dietary Consumption Patterns” Stephen E. Fienberg and Rebecca C. Steorts; 95-96
• Contribution M. A. Girolami; 97
• Wonderful Examples, but Let’s not Close Our Eyes David J. Hand; 98-100
• Discussion A. H. Welsh; 101-102
• Reply to the Discussion of “Estimating the Distribution of Dietary Consumption Patterns” Raymond J. Carroll; 103
• Response to Discussion by A. H. Welsh on the AF 447 Paper Lawrence D. Stone; 104-105

Séminaire Probabilités, Décision, Incertitude

Last Friday, I gave a seminar at the Séminaire Probabilités, Décision, Incertitude, which is run by IHφST, the institute for history and philosophy of sciences and techniques of the Université of Paris 1. I decided to present my Budapest EMS 2013 talk at a slower pace and by cutting the technical parts. And adding a few historical titbits. It took me two hours and I enjoyed the experience. I cannot tell for the audience, who seemed a bit wary of mathematical disgressions, but I got comments on the Lindley paradox and on the contents of Ari Spanos’ Who’s afraid… Here are the slides again, in case Slideshare freezes your browser as it does mine…

As a side anecdote, the seminar took place in an old building in the core of the Saint-Germain des Prés district. The view from the seminar room on the busy streets of this district was quite eye-catching! (Not as distracting as the one from a room in Ca’ Foscari where I gave a seminar a few years ago facing the Venezia Laguna and windsurfers practising…)

Bayes-250

My fourth Bayes-250 and presumably the last one, as it starts sounding like groundhog day!

Stephen Stigler started the day with three facts or items of inference on Thomas Bayes: the first one was about The Essay and its true title, a recent research I made use of in Budapest. As reported in his Statistical Science paper, Stigler found an off-print of Bayes’ Essay with an altogether different title: “A Method of Calculating the Exact Probability of All Conclusions founded on Induction”, which sounds much better than the title of the version published in the Proceedings of the Royal Society, “An Essay toward solving a Problem in the Doctrine of Chances”, and appears as part of a larger mathematical construct in answering Hume’s dismissal of miracles… (Dennis Lindley in a personal communication to Stephen acknowledged the importance of the title and regretted “as an atheist” that the theorem was intended for religious usage!)

Stephen then discussed Bayes’s portrait, which (first?) appeared in June 1933 in The American Conservationist. Herein acknowledged as taken from the Wing collection of the Newberry library in Chicago (where Stephen has not yet unearthed the said volume!) My suggestion would be to use a genealogy algorithm to check whether or not paternity cannot be significantly rejected by comparing the two portraits. The more portraits from Bayes’ family, the better.

Steven Fienberg took over for another enjoyable historical talk about the neo-Bayesian revival of the 50s. In connection with his BA paper on the appearance of the term Bayesian. Giving appropriately a large place to Alan Turing. And Jimmy Savage (whose book does not use the term Bayesian). He also played great videos of Howard Raiffa explaining how he became a (closet) Bayesian. And of Jack Good being interviewed by Persi Diaconis. (On a highly personal level, I wonder who in my hotel has named his or her network “Neo Bayesian Revival”!)

In a very unusual format, Adrian Smith and Alan Gelfand ran an exchange around a bottle of Scotch (and a whole amphitheatre), where Adrian recollected his youth at Cambridge and the slow growth of Bayesian statistics in the UK (“a very unorthodox form of inference” in Dennis’ words). I liked very much the way he explained how Dennis Lindley tried to build for statistics the equivalent of the system of axioms Kolmogorov had produced for probability. And even more how Dennis came to the Bayesian side for decision-theoretic reasons. (The end of the exchange was more predictable as being centred on the MCMC revolution.)

Michael Jordan completed the day with a talk oriented much more towards the future. About the growing statistical perspective on document analysis. Document as data indeed. Starting with the bag of words representation. (A side remark was that his paper Latent Dirichlet allocation got more citations than classics like Jim Berger’s 1985 book or Efron’s 1984 book.) The central theme of the talk was that there is much work left to be done to address real problems. Really real problems with computational issues orders of magnitude away from what we can propose today. Michael took linguistics as a final example. Linking with Adrian’s conclusion in that respect.

Dennis Lindley (1923-2013)

Dennis Lindley most sadly passed away yesterday at the hospital near his home in Somerset. He was one of the founding fathers of our field (of Bayesian statistics), who contributed to formalise Bayesian statistics in a coherent theory. And to make it one with rational decision-making, a perspective missing in Jeffreys’ vision. (His papers figured prominently in the tutorials we gave yesterday for the opening of O’Bayes 250.) At the age of 90, his interest in the topic had not waned away: as his interview with Tony O’Hagan last Spring showed, his passionate arguing for the rationale of the Bayesian approach was still there and alive! The review he wrote of The Black Swan a few years ago also demonstrated he had preserved his ability to see through bogus arguments. (See his scathing “One hardly advances the respect with which statisticians are held in society by making such declarations” in his ripping discussion of Aitkin’s 1991 Posterior Bayes factors.) He also started this interesting discussion last year about the five standard deviations “needed” for the Higgs boson…  My personal email contacts with Dennis over the re-reading of Jeffreys’ book  were a fantastic experience as he kindly contributed by expanding on how the book was received at the time and correcting some of my misunderstanding. It is a pity I can no longer send him the (soon to come?) final version of my Jeffreys-Lindley paradox paper as I intended to do. The email thomasbayes@gmail.com will no longer answer our queries… I figure there will be many testimonies and shared memories of his contributions and life at the Bayes-250 conference tomorrow. Farewell, Dennis, and I hope you now explore the paths of a more coherent world than ours!