Archive for SuSTain

structure and uncertainty, Bristol, Sept. 26

Posted in Books, pictures, R, Running, Statistics, Travel, University life, Wines with tags , , , , , , , , , , , , , , on September 27, 2012 by xi'an

Another day full of interesting and challenging—in the sense they generated new questions for me—talks at the SuSTain workshop. After another (dry and fast) run around the Downs; Leo Held started the talks with one of my favourite topics, namely the theory of g-priors in generalized linear models. He did bring a new perspective on the subject, introducing the notion of a testing Bayes factor based on the residual statistic produced by a classical (maximum likelihood) analysis, connected with earlier works of Vale Johnson. While I did not truly get the motivation for switching from the original data to this less informative quantity, I find this perspective opening new questions for dealing with settings where the true data is replaced with one or several classical statistics. With possible strong connections to ABC, of course. Incidentally, Leo managed to produce a napkin with Peter Green’s intro to MCMC dating back from their first meeting in 1994: a feat I certainly could not reproduce (as I also met both Peter and Leo for the first time in 1994, at CIRM)… Then Richard Everit presented his recent JCGS paper on Bayesian inference on latent Markov random fields, centred on the issue that simulating the latent MRF involves an MCMC step that is not exact (as in our earlier ABC paper for Ising models with Aude Grelaud). I already discussed this paper in an earlier blog and the only additional question that comes to my mind is whether or not a comparison with the auxiliary variable approach of Møller et al. (2006) would make sense.

In the intermission, I had a great conversation with Oliver Ratman on his talk of yesterday on the surprising feature that some models produce as “data” some sample from a pseudo-posterior.. Opening once again new vistas! The following talks were more on the mathematical side, with James Cussens focussing on the use of integer programming for Bayesian variable selections, then Éric Moulines presenting a recent work with a PhD student of his on PAC-Bayesian bounds and the superiority of combining experts. Including a CRAN package. Éric concluded his talk with the funny occurence of Peter’s photograph on Éric’s Microsoft Research Profile own page, due to Éric posting our joint photograph at the top of Pic du Midi d’Ossau in 2005… (He concluded with a picture of the mountain that was the exact symmetry of mine yesterday!)

The afternoon was equally superb with Gareth Roberts covering fifteen years of scaling MCMC algorithms, from the mythical 0.234 figure to the optimal temperature decrease in simulated annealing, John Kent playing the outlier with an EM algorithm—however including a formal prior distribution and raising the challenge as to why Bayesians never had to constrain the posterior expectation, which prompted me to infer that (a) the prior distribution should include all constraints and (b) the posterior expectation was not the “right” tool in non-convex parameters spaces—. Natalia Bochkina presented a recent work, joint with Peter Green, on connecting image analysis with Bayesian asymptotics, reminding me of my early attempts at reading Ibragimov and Has’minskii in the 1990’s. Then a second work with Vladimir Spoikoini on Bayesian asymptotics with misspecified models, introducing a new notion of effective dimension. The last talk of the day was by Nils Hjort about his coming book on “Credibility, confidence and likelihood“—not yet advertised by CUP—which sounds like an attempt at resuscitating Fisher by deriving distributions in the parameter space from frequentist confidence intervals. I already discussed this notion in an earlier blog, so I am fairly skeptical about it, but the talk was representative of Nils’ highly entertaining and though-provoking style! Esp. as he sprinkled the talk with examples where MLE (and some default Bayes estimators) did not work. And reanalysed one of Chris Sims‘ example presented during his Nobel Prize talk…

Structure and uncertainty, Bristol, Sept. 25

Posted in pictures, Running, Statistics, Travel, Uncategorized, University life with tags , , , , , , , , , on September 26, 2012 by xi'an

This was a fairly full day at the Structure and uncertainty modelling, inference and computation in complex stochastic systems workshop! After a good one hour run around the Clifton Down, the morning was organised around likelihood-free methods, mostly ABC, plus Arnaud Doucet’s study of methods based on unbiased estimators of the likelihood (à la Beaumont, with the novelty of assessing the inefficiency due to the estimation, really fascinating..). The afternoon was dedicated to graphical models. Nicolas Chopin gave an updated version of his Kyoto talk on EP-ABC where he resorted to composite likelihoods for hidden Markov models, (I then wondered about the parameterisation and the tolerance determination for this algorithm.) Oliver Ratman presented some of the work he did on the flu while in Duke, then move to a new approach for ABC tolerance based on various kinds of testing (which I found clearer than in Kyoto, maybe because I was not jet-lagged!) And I gave my talk on ABC-EL.I found the afternoon session harder to follow, mostly because I always have trouble understanding the motivations and the notations used on these models, albeit fascinating. I remained intrigued by the bidirectional dependence arrow in those graphs for the whole afternoon (even though I think I get it now!) After looking at the few posters presented this afternoon, I went for another short run in Leigh Woods, before joining a group of friends for an Indian dinner at the Brunel Raj. A very full day…!

Structure and uncertainty, Bristol, Sept. 24-27

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , on September 25, 2012 by xi'an

I am back in Bristol just a few months after an earlier SuSTain workshop. (During my Spring UK trip to Bristol, Glasgow, and Edinburgh…) The theme of the workshop is Structure and uncertainty modelling, inference and computation in complex stochastic systems. And it enjoys a very rich program over the four days! I am talking about ABC and empirical likelihood, with the following slides I just completed:

Unsurprisingly, those slides borrow both from my earlier talks in Kyoto and Australia, and from Pierre Purdlo’s earlier talk on this paper… (I also added pictures of some of the hikes and climbs Peter Green and I survived together!)

I alas arrived too late for today’s sessions, having to give the opening lecture at my Statistics Master in Paris-Dauphine. (I will also alas miss half of Thursday’s talks!) As I am staying at the Avon Gorge Hotel, just next to the bridge, I took the opportunity of some remaining daylight to go running across Brunel’s bridge and into the nearby park of Leigh Woods. It happened to be very muddy thanks to the torrential rains of the morning, but it was a good way to test my recovering knee (after a minor bike fall last week!) on a long run… And it apparently held, although tomorrow morning run will tell for sure.

semi-automatic ABC [reply]

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , on June 5, 2012 by xi'an

When I came back from LGM2012 in Trondheim, I found the latest issue of Series B on my desk. It is much thicker than in “my” days, with about 250 pages in this June 2012 issue! (One reason is that it contains two Read Papers with their discussions, amounting to 110 pages of the journal.) The first Read Paper was “Catching up faster by switching sooner” by van Erven, Grünwald and de Rooij, that we discussed with Nicolas Chopin. There are also comments (among others!) from Stephen Lauritzen, Iain Murray, and Aki Vehtari, who also spoke about Bayesian model evaluation tools at LGM2012. The second Read Paper is Fearnhead’s and Prangle’s semi-automatic ABC that I discussed last December. I have already posted about this Read Paper and used some of the discussion in preparing my ABC PhD class in Roma.  However, the remark we made in our discussion with Jean-Michel Marin that the Bayes factor would not be a pertinent summary statistic for model choice is wrong, as shown by Dennis Prangle in his poster at the workshop in Bristol. And, when reading the reply by Paul Fearnhead and Dennis Prangle, I do not see a satisfactory answer to my demand of more formal conditions for Theorem 2 and its corollary, the convergence of the noisy ABC posterior to the true parameter (page 425), to apply. (Such results exist in indirect inference.)

Hamilton confronting intractability (with a li’le help from Metropolis)

Posted in Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , , , on April 20, 2012 by xi'an

Last day of a great workshop! I filled more pages of my black notebook (“bloc”) than in the past month!!! This morning started with an Hamiltonian session, Paul Fearnhead presenting recent developments in this area. I liked his coverage very much, esp. because it went away from the physics analogies that always put me off. The idea of getting away from the quadratic form had always seemed natural to me and provided an interesting range for investigations. (I think I rediscovered the topic during the talks, rephrasing almost the same questions as for Girolami’s and Calderhead’s Read Paper!) One thing that still intrigues me is the temporal dimension of the Hamiltonian representation. Indeed, it is “free” in the sense that the simulation problem does not depend on the time the pair (x,p) is moved along the equipotential curve. (In practice, there is a cost in running this move because it needs to be discretised.) But there is no clear target function to set the time “right”. The only scale I can think of is when the pair comes back by its starting point. Which is less silly than it sounds because the discretisation means that all intermediate points can be used, as suggested by Paul via a multiple try scheme. Mark then presented an application of Hamiltonian ideas and schemes to biochemical dynamics, with a supplementary trick of linearisation. Christian Lorenz Müller gave an ambitious grand tour of gradient free optimisation techniques that sounded appealing from a simulation perspective (but would require a few more hours to apprehend!), Geoff Nicholls presented on-going research on approximating Metropolis-Hastings acceptance probabilities in a more general perspective than à la Andrieu-Robert, i.e. accepting some amount of bias, an idea he has explained to me when I visited Oxford. And Pierre Jacob concluded the meeting in the right tone with a pot-pourri of his papers on Wang-Landau. (Once again a talk I had already heard but that helped me make more sense of a complex notion…)

Overall and talk-by-talk, a truly exceptional meeting. Which also set the bar quite high for us to compete at the ICMS meeting on advances in MCM next Monday! Esp. when a portion of the audience in Bristol will appear in Edinburgh as well!an In the meanwhile, I have to rewrite my talk for the seminar in Glasgow tomorrow in order to remove the overlap with my talk there last year(I note that I have just managed to fly to Scotland with no lost bag, a true achievement!)