Archive for Big’MC

last Big MC [seminar] before summer [June 19, 3pm]

Posted in pictures, Statistics, University life with tags , , , , , , , , , , , on June 17, 2014 by xi'an

crossing Rue Soufflot on my way to IHP from Vieux Campeur, March 28, 2013Last session of our Big’MC seminar at Institut Henri Poincaré this year, on Tuesday Thursday, June 19, with

Chris Holmes (Oxford) at 3pm on

Robust statistical decisions via re-weighted Monte Carlo samples

and Pierre Pudlo (iC3M, Université de Montpellier 2) at 4:15pm on [our joint work]

ABC and machine learning

Luke and Pierre at big’MC

Posted in Linux, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on May 19, 2014 by xi'an

crossing Rue Soufflot on my way to IHP from Vieux Campeur, March 28, 2013Yesterday, Luke Bornn and Pierre Jacob gave a talk at our big’MC ‘minar. While I had seen most of the slides earlier, either at MCMski IV,  Banff, Leuven or yet again in Oxford, I really enjoyed those talks as they provided further intuition about the techniques of Wang-Landau and non-negative unbiased estimators, leading to a few seeds of potential ideas for even more potential research. For instance, I understood way better the option to calibrate the Wang-Landau algorithm on levels of the target density rather than in the original space. Which means (a) a one-dimensional partition target (just as in nested sampling); (b) taking advantage of the existing computations of the likelihood function; and (b) a somewhat automatic implementation of the Wang-Landau algorithm. I do wonder why this technique is not more popular as a default option. (Like, would it be compatible with Stan?) The impossibility theorem of Pierre about the existence of non-negative unbiased estimators never ceases to amaze me. I started wondering during the seminar whether a positive (!) version of the result could be found. Namely, whether perturbations of the exact (unbiased) Metropolis-Hastings acceptance ratio could be substituted in order to guarantee positivity. Possibly creating drifted versions of the target…

One request in connection with this post: please connect the Institut Henri Poincaré to the eduroam wireless network! The place is dedicated to visiting mathematicians and theoretical physicists, it should have been the first one [in Paris] to get connected to eduroam. The cost cannot be that horrendous so I wonder what the reason is. Preventing guests from connecting to the Internet towards better concentration? avoiding “parasites” taking advantage of the network? ensuring seminar attendees are following the talks? (The irony is that Institut Henri Poincaré has a local wireless available for free, except that it most often does not work with my current machine. And hence wastes much more of my time as I attempt to connect over and over again while there.) Just in connection with IHP, a video of Persi giving a talk there about Poincaré, two years ago:

big’MC’minar next week

Posted in Kids, Statistics, Travel, University life with tags , , , , , , , on May 9, 2014 by xi'an

crossing Rue Soufflot on my way to IHP from Vieux Campeur, March 28, 2013The next big’MC seminar in Paris will be delivered on Thursday, May 15, by

15 h : Luke Bornn, Towards the Derandomization of Markov chain Monte Carlo

16 h 15 : Pierre Jacob, On exact inference and unbiased estimation 

see the seminar webpage for more details. And make sure to attend if in or near Paris! It is definitely big and MC. Most sadly (for us!), Chris Holmes will give a Smile (Statistical machine learning) seminar at the very same time a few streets away…  At least, we can conveniently meet right after for a drink!

big’MC seminar next week

Posted in Statistics, University life with tags , , , , on October 8, 2013 by xi'an

The big’MC seminar in Paris will be delivered on Thursday, October 17 by

15 h : Sylvain Le Corff  Continuous-time importance sampling for Jump diffusions

16 h 15 : Yohan Petetin  Single- and multiple-object filtering for Markov models with jumps
see the seminar webpage for more details.

Olli à/in/im Paris

Posted in Statistics, Travel, University life with tags , , , , , , , , , , , , on May 27, 2013 by xi'an

Warning: Here is an old post from last October I can at last post since Olli just arXived the paper on which this talk was based (more to come, before or after Olli’s talk in Roma!).

Oliver Ratman came to give a seminar today at our Big’MC seminar series. It was an extension of the talk I attended last month in Bristol:

10:45 Oliver Ratmann (Duke University and Imperial College) – “Approximate Bayesian Computation based on summaries with frequency properties”

Approximate Bayesian Computation (ABC) has quickly become a valuable tool in many applied fields, but the statistical properties obtained by choosing a particular summary, distance function and error threshold are poorly understood. In an effort to better understand the effect of these ABC tuning parameters, we consider summaries that are associated with empirical distribution functions. These frequency properties of summaries suggest what kind of distance function are appropriate, and the validity of the choice of summaries can be assessed on the fly during Monte Carlo simulations. Among valid choices, uniformly most powerful distances can be shown to optimize the ABC acceptance probability. Considering the binding function between the ABC model and the frequency model of the summaries, we can characterize the asymptotic consistency of the ABC maximum-likelhood estimate in general situations. We provide examples from phylogenetics and dynamical systems to demonstrate that empirical distribution functions of summaries can often be obtained without expensive re-simulations, so that the above theoretical results are applicable in a broad set of applications. In part, this work will be illustrated on fitting phylodynamic models that capture the evolution and ecology of interpandemic influenza A (H3N2) to incidence time series and the phylogeny of H3N2’s immunodominant haemagglutinin gene.

I however benefited enormously from hearing the talk again and also from discussing the fundamentals of his approach before and after the talk (in the nearest Aussie pub!). Olli’s approach is (once again!) rather iconoclastic in that he presents ABC as a testing procedure, using frequentist tests and concepts to build an optimal acceptance condition. Since he manipulates several error terms simultaneously (as before), he needs to address the issue of multiple testing but, thanks to a switch between acceptance and rejection, null and alternative, the individual α-level tests get turned into a global α-level test.