Fig. 4 – Boxplots of the evolution [against ε] of ABC approximations to the Bayes factor. The representation is made in terms of frequencies of visits to [accepted proposals from] models MA(1) and MA(2) during an ABC simulation when ε corresponds to the 10,1,.1,.01% quantiles on the simulated autocovariance distances. The data is a time [...] [Read more...]

Pierre Pudlo and I worked this morning on a distribution related to philogenic trees and got stuck on the following Bessel integral where In is the modified Bessel function of the first kind. We could not find better than formula 6.611(4) in Gradshteyn and Ryzhik. which is for a=0… Anyone in ... [Read more...]

At JSM, John Kimmel gave me a copy of the Handbook of Markov chain Monte Carlo, as I had not (yet?!) received it. This handbook is edited by Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng, all first-class jedis of the MCMC galaxy. I had not had a chance ... [Read more...]

After a terrific run this morning to the top of Arthur’s Seat, and then around (the ribs are feeling fine, now!), the Bayes-250 talks were exhilarating and challenging. Jim Smith gave an introduction to the challenges of getting different experts to collaborate on a complex risk assessment, much in ... [Read more...]

“It seems quite absurd to reject an EP-based approach, if the only alternative is an ABC approach based on summary statistics, which introduces a bias which seems both larger (according to our numerical examples) and more arbitrary, in the sense that in real-world applications one has little intuition and even ... [Read more...]

I just got the following email from PNAS about our Lack of confidence in ABC model choice. Editor's Remarks to Author: both referees now find the manuscript acceptable for publication as do I. Each suggests small changes which I encourage the authors to make prior to having the manuscript go ... [Read more...]

Yesterday, we had a meeting of our EMILE network on statistics for population genetics (in Montpellier) and we were discussing our respective recent advances in ABC model choice. One of our colleagues mentioned the constant request (from referees) to include the post-ABC processing devised by Fagundes et al. in their 2007 ... [Read more...]

Following my earlier posts on the revision of Lack of confidence, here is an interesting outcome from the derivation of the exact marginal likelihood in the Laplace case. Computing the posterior probability of a normal model versus a Laplace model in the normal (gold) and the Laplace (chocolate) settings leads ... [Read more...]

In conjunction with the normal-Laplace comparison mentioned in the most recent post about our lack of confidence in ABC model choice, we have been working on the derivation of the exact Bayes factor and I derived an easy formula for the marginal likelihood in the Laplace case that boils down ... [Read more...]

Yesterday, Andrew Thomas and José Blanchet posted a note on the Bernouilli factory on arXiv. This short paper links with the recent paper of Flegal and Herbei I commented earlier. Considering the special target Thomas and Blanchet develop an elaborate scheme of cascading envelopes that converge to f from above. ... [Read more...]

“We don’t need likelihood functions; we just need to know how to simulate from [them] (…) We don’t need models with sufficient statistics; we just need summary statistics (…) We don’t need to be Bayesian; we just need to be approximately so. We don’t need theory to tell ... [Read more...]

Yet another paper on ABC model choice was posted on arXiv a few days ago, just prior to the ABC in London meeting that ended in the pub above (most conveniently located next to my B&B!). It is written by Olivier Francois and Guillaume Laval and the approach relies ... [Read more...]

Following the comments on our earlier submission to PNAS, we have written (and re-arXived) a revised version where we try to spell out (better) the distinction between ABC point (and confidence) estimation and ABC model choice, namely that the problem was at another level for Bayesian model choice (using posterior ... [Read more...]

I received this email last week from Ian Langmore, a postdoc in Columbia: I’m looking for literature on a subject and can’t find it:  I have a Metropolis sampler where the acceptance probability is evaluated with some error.  This error is not simply error in evaluation of the ... [Read more...]

TOMACS (ACM Transactions on Modeling and Computer Simulation) is launching a call for paper submission. The special topic is Monte Carlo Methods in Statistics and Arnaud Doucet and myself are the special issue editors. Here are the details.: Over the last two decades Monte Carlo methods have attracted much attention ... [Read more...]

Statistics and Computing has received several papers on ABC and plans to make a special ABC issue out of these. All submissions prior to June 2011 that will be accepted will be published in this special issue. The special issue is identified as an article type on the on-line page. In ... [Read more...]

After the very exciting and I think quite successful ABC in Paris meeting two years ago, Michael Stumpf from Imperial College London suggested a second edition in London along the same lines. Michael kindly associated me with the planning of this meeting. It is (logically) called ABC in London (or ... [Read more...]

I am in Montpellier today for a general meeting of our EMILE ANR grant bi-yearly meeting, discussing ABC model choice and new applications of simulation methods in population genetics, including an upgrade of DIYABC into the 2.0 version. (The above is a picture comparing “true” Bayes factors with ABC versions, commented ... [Read more...]

The second day at the Latent Gaussian Models workshop in Zürich was equally interesting. Among the morning talks, let me mention Daniel Bové who gave a talk connected with the hyper-g prior paper he wrote with Leo Held (commented in an earlier post) and the duo of Janine Illian ... [Read more...]

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