Matthew Hoffman and Andrew Gelman have posted a paper on arXiv entitled “The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo” and developing an improvement on the Hamiltonian Monte Carlo algorithm called NUTS (!). Here is the abstract: Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) ... [Read more...]

Erkan Buzbas sent me an email about his webpage (operated as a wordpress blog) on ABC. It contains different items of information on ABC research and an hopefully growing list of references. After Scott Sisson’s tweet on ABC_research (latest news: two ABC sessions in ISBA 20122, Kyoto),  here comes ... [Read more...]

Yes, yet another Bayesian textbook: Ioannis Ntzoufras’ Bayesian modeling using WinBUGS was published in 2009 and it got an honourable mention at the 2009 PROSE Award. (Nice acronym for a book award! All the mathematics books awarded that year were actually statistics books.) Bayesian modeling using WinBUGS is rather similar to the ... [Read more...]

As supplementary material to the ABC paper we just arXived, here is the R code I used to produce the Bayes factor comparisons between summary statistics in the normal versus Laplace example. (Warning: running the R code takes a while!) Filed under: R, Statistics, University life Tagged: ABC, Bayesian model ... [Read more...]

Here is [yet!] another Bayesian textbook that appeared recently. I read it in the past few days and, despite my obvious biases and prejudices, I liked it very much! It has a lot in common (at least in spirit) with our Bayesian Core, which may explain why I feel so ... [Read more...]

I just got the “news” that Dennis Ritchie died, although this happened on October 12… The announcement was surprisingly missing from my information channels and certainly got little media coverage, compared with Steve Jobs‘ demise. (I did miss the obituaries in the New York Times and in the Guardian. The Economist ... [Read more...]

Here is our discussion (with Nicolas Chopin) of the Read Paper of last Wednesday by T. van Erven, P. Grünwald and S. de Rooij (Centrum voor Wiskunde en Informatica, Amsterdam), entitled Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the Akaike ... [Read more...]

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...]

Bill Bolstad wrote a reply to my review of his book Understanding computational Bayesian statistics last week and here it is, unedited except for the first paragraph where he thanks me for the opportunity to respond, “so readers will see that the book has some good features beyond having a “... [Read more...]

There is a call for postdoctoral positions supported by the Paris Mathematical Sciences Foundation. The deadline is December 13 and the on-line application is available. If you are interested in working with me on Bayesian statistics  (model choice, time series model) or computational methods (SMC, MCMC, ABC, &c.) thru this call, ... [Read more...]

Pierre Jacob and Robin Ryder (from Paris-Dauphine, CREST, and Statisfaction) have just arXived (and submitted to the Annals of Applied Probability) a neat result on the Wang-Landau algorithm. (This algorithm, which modifies the target in a sort of reweighted partioned sampling to achieve faster convergence, has always been perplexing to ... [Read more...]

“Bayes Theorem is a simple consequence of the axioms of probability, and is therefore accepted by all as valid. However, some who challenge the use of personal probability reject certain applications of Bayes Theorem.“  J. Kadane, p.44 Principles of uncertainty by Joseph (“Jay”) Kadane (Carnegie Mellon University, Pittsburgh) is a ... [Read more...]

The two translators of our book in Japanese, Kazue & Motohiro Ishida, contacted me about some R code mistakes in the book. The translation is nearly done and they checked every piece of code in the book, an endeavour for which I am very grateful! Here are the two issues they ... [Read more...]

I have just finished reading this book by Bill Bolstad (University of Waikato, New Zealand) which a previous ‘Og post pointed out when it appeared, shortly after our Introducing Monte Carlo Methods with R. My family commented that the cover was nicer than those of my own books, which is ... [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...]

Although this was only a half-day of talks, the third day of the workshop was equally thought-challenging and diverse.  (I managed to miss the ten first minutes by taking a Line 3 train to 125th street, having overlooked the earlier split from Line 1… Crossing south Harlem on a Sunday morning is ... [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...]

Julien Cornebise has [once again!] pointed out a recent Guardian article. It is about commercial publishers of academic journals, mainly Elsevier, Springer, and Wiley, with a clear stand from its title: “Academic publishers make Murdoch look like a socialist“! The valuable argument therein is that academic publishers make hefty profits (... [Read more...]

Julien Cornebise pointed me to this Guardian article that itself summarises the findings of a Nature Neuroscience article I cannot access. The core of the paper is that a large portion of comparative studies conclude to a significant difference between protocols when one protocol result is significantly different from zero ... [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...]