Archive for Glasgow
Above is the solution produced by a team at the University of Waterloo to the travelling salesman problem of linking all pubs in the UK (which includes pubs in Northern Ireland as well as some Scottish islands—even though I doubt there is no pub at all on the Island of Skye! They also missed a lot of pubs in Glasgow! And worst gaffe of all, they did not include the Clachaigh Inn, probably the best pub on Earth…). This path links over 24 thousand pubs, which is less than the largest travelling salesman problem solved at the current time, except that this case used the exact distances provided by Google maps. Of course, it would somehow make more sense to increase the distances by random amounts as the pub visits increase, unless the visitor sticks to tonic. Or tea.
A new Rankin, a new Rebus! (New as in 2015 since I waited to buy the paperback version.) Sounds like Ian Rankin cannot let his favourite character rest for his retirement and hence set in back into action, along with the new Malcom Fox [working in the Complaints] and most major characters of the Rebus series. Including the unbreakable villain, Big Ger Cafferty. This as classical as you get, borrows from half a dozen former Rebus novels, not to mention this neo-Holmes novel I reviewed a while ago. But it is gritty, deadly efficient and captivating. I read the book within a few days from returning from Warwick.
About the title, this is a song by The Associates that plays a role in the book. I did not this band, but looking for it got me to a clip that used an excerpt from the Night of the Hunter. Fantastic movie, one of my favourites.
I just heard that Peter Hall passed away yesterday in Melbourne. Very sad news from down under. Besides being a giant in the fields of statistics and probability, with an astounding publication record, Peter was also a wonderful man and so very much involved in running local, national and international societies. His contributions to the field and the profession are innumerable and his loss impacts the entire community. Peter was a regular visitor at Glasgow University in the 1990s and I crossed paths with him a few times, appreciating his kindness as well as his highest dedication to research. In addition, he was a gifted photographer and I recall that the [now closed] wonderful guest-house where we used to stay at the top of Hillhead had a few pictures of his taken in the Highlands and framed on its walls. (If I remember well, there were also beautiful pictures of the Belgian countryside by him at CORE, in Louvain-la-Neuve.) I think the last time we met was in Melbourne, three years ago… Farewell, Peter, you certainly left an indelible print on a lot of us.
[Song Chen from Beijing University has created a memorial webpage for Peter Hall to express condolences and share memories.]
As much as I love Scotland, or because of it, I would not dream of suggesting to Scots that one side of the referendum sounds better than the other. However, I am rather annoyed at the yoyo-like reactions to the successive polls about the result, because, just like during the US elections, each poll is analysed separately rather than being pooled with the earlier ones in a reasonable meta-analysis… Where is Nate Silver when we need him?!
Deborah Mayo wrote a Saturday night special column on our Big Bayes stories issue in Statistical Science. She (predictably?) focussed on the critical discussions, esp. David Hand’s most forceful arguments where he essentially considers that, due to our (special issue editors’) selection of successful stories, we biased the debate by providing a “one-sided” story. And that we or the editor of Statistical Science should also have included frequentist stories. To which Deborah points out that demonstrating that “only” a frequentist solution is available may be beyond the possible. And still, I could think of partial information and partial inference problems like the “paradox” raised by Jamie Robbins and Larry Wasserman in the past years. (Not the normalising constant paradox but the one about censoring.) Anyway, the goal of this special issue was to provide a range of realistic illustrations where Bayesian analysis was a most reasonable approach, not to raise the Bayesian flag against other perspectives: in an ideal world it would have been more interesting to get discussants produce alternative analyses bypassing the Bayesian modelling but obviously discussants only have a limited amount of time to dedicate to their discussion(s) and the problems were complex enough to deter any attempt in this direction.
As an aside and in explanation of the cryptic title of this post, Deborah wonders at my use of endemic in the preface and at the possible mis-translation from the French. I did mean endemic (and endémique) in a half-joking reference to a disease one cannot completely get rid of. At least in French, the term extends beyond diseases, but presumably pervasive would have been less confusing… Or ubiquitous (as in Ubiquitous Chip for those with Glaswegian ties!). She also expresses “surprise at the choice of name for the special issue. Incidentally, the “big” refers to the bigness of the problem, not big data. Not sure about “stories”.” Maybe another occurrence of lost in translation… I had indeed no intent of connection with the “big” of “Big Data”, but wanted to convey the notion of a big as in major problem. And of a story explaining why the problem was considered and how the authors reached a satisfactory analysis. The story of the Air France Rio-Paris crash resolution is representative of that intent. (Hence the explanation for the above picture.)
In a “crazy travelling week” (dixit my daughter), I gave a talk at an IYS 2013 conference organised by Stephen Senn (formerly at Glasgow) and colleagues in the city of Luxembourg, Grand Duché du Luxembourg. I enjoyed very much the morning train trip there as it was a misty morning, with the sun rising over the frosted-white countryside. (I cannot say much about the city of Luxembourg itself though as I only walked the kilometre from the station to the conference hotel and the same way back. There was a huge gap on the plateau due to a river in the middle, which would have been a nice place to run, I presume…)
One of the few talks I attended there was about an econometric model with instrumental variables. In general, and this dates back to my student’s years at ENSAE, I do not get the motivation for the distinction between endogenous and exogenous in econometrics models. Especially in non-parametric models as, if we do not want to make parametric assumptions, we have difficulties in making instead correlation hypotheses… My bent would be to parametrise everything under the suspicion of this everything being correlated with everything. The instrumental variables econometricians seem so fond of appear to me like magical beings, since we have to know they are instrumental. And because they seem to allow to always come back to a linear setting, by eliminating the non-linear parts. Sounds like a “more for less” free-lunch deal. (Any pointer would be appreciated.) The speaker there actually acknowledged (verbatim) that they are indeed magical and that they cannot be justified by mathematics or statistics. A voodoo part of econometrics then?!
A second talk that left me perplexed was about a generalised finite mixture model. The model sounded like a mixture along time of individuals, ie a sort of clustering of longitudinal data. It looked like it should be easier to estimate than usual mixtures of regressions because an individual contributed to the same regression line for all the times when it was observed. The talk was uninspiring as it missed connections to EM and to Bayesian solutions, focussing instead on a gradient method that sounded inappropriate for a multimodal likelihood. (Funny enough, the choice in the number of regressions was done by BIC.)