Archive for Sherbrooke

the last digit of e

Posted in Kids, Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , on March 3, 2016 by xi'an

Éric Marchand from Sherbrooke, Québec [historical birthplace of MCMC, since Adrian Smith gave his first talk on his Gibbs sampler there, in June 1989], noticed my recent posts about the approximation of e by Monte Carlo methods and sent me a paper he wrote in The Mathematical Gazette of November 1995 [full MCMC era!] about original proofs on the expectation of some stopping rules being e, like the length of increasing runs. And Gnedenko’s uniform summation until exceeding one. Amazing that this simple problem generated so much investigation!!!

the biggest change

Posted in Statistics, University life with tags , , , , , , on September 29, 2011 by xi'an

The current question for the ISBA Bulletin is “What is the biggest and most surprising change in the field of Statistics that you have witnessed, and what do you think will be the next one?” The answer to the second part is easy: I do not know and even if I knew I would be writing papers about it rather than spilling the beans… The answer to the first part is anything but easy. At the most literal level, taking “witnessed” at face value, I have witnessed the “birth” of Markov chain Monte Carlo methods at the conference organised in Sherbrooke by Jean-Francois Angers in June 1989… (This was already reported in our Short history of MCMC with George Casella.) I clearly remember Adrian showing the audience a slide with about ten lines of Fortran code that corresponded to the Gibbs sampler for a Bayesian analysis of a mixed effect linear model (later to be analysed in JASA). This was so shockingly simple… It certainly was the talk that had the most impact on my whole career, even though (a) I would have certainly learned about MCMC quickly enough had I missed the Sherbrooke conference and (b) there were other talks in my academic life that also induced that “wow” moment, for sure. At a less literal level, the biggest chance if not the most surprising is that the field has become huge, multifaceted, and ubiquitous. When I started studying statistics, it was certainly far from being the sexiest possible field! (At least in the general public) And the job offers were not as numerous and diverse as they are today. (The same is true for Bayesian statistics, of course. Even though it has sounded sexy from the start!)