Similar to last year, I am giving a series of lectures on simulation jointly as a Master course in Paris-Dauphine and as a 3rd year course in ENSAE. The course borrows from both the books Monte Carlo Statistical Methods and from Introduction to Monte Carlo Methods with R, with George ... [Read more...]

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. ... [Read more...]

Another full day spent working with Jean-Michel Marin on the new edition of Bayesian Core (soon to be Bayesian Essentials with R!) and the remaining hierarchical Bayes chapter… I have reread and completed the regression and GLM chapters, sent to very friendly colleagues for a last round of comments. Now, ... [Read more...]

Among the books I received for review in CHANCE, here are some neither I nor my “usual suspects” had enough time or interest in to review: R Graphics (second edition) by Paul Murrell Biostatistics: A computing approach by Stewart Anderson Advanced Bayesian methods for medical test accuracy by Lyle Broemeling ... [Read more...]

Jean-Michel Marin visited me in Paris last week and, besides taking part in Pierre’s PhD defence, we made enough progress to close two more chapters of the new edition of Bayesian Core (soon to be Bayesian Essentials with R!) This follows the good work session we had in Carnon ... [Read more...]

After a sunny weekend to unpack and unwind, I am now back to my normal schedule, on my way to Paris-Dauphine for an R (second-chance) exam. Except for confusing my turn signal for my wiper, thanks to two weeks of intensive driving in four Australian states!, things are thus back ... [Read more...]

Here are the slides for the second day of my course at Monash University, Melbourne, in the Special Lectures in Econometrics, with a strong strong similarity with the slides of my course in Roma this Spring. (Ah, sunny Roma…) The first day lecture was very well attended and I hope ... [Read more...]

Here are the slides for the first day of my course at Monash University, Melbourne, in the Special Lectures in Econometrics, with a strong similarity with the slides of my course in Wharton, two years ago. (Be sure to check slide 67! If the update on slideshare works from my flat ... [Read more...]

I list and discuss the three books on Bayesian analysis that I recommend to social scientists. [Read more...]

Yet another full day working on Bayesian Core with Jean-Michel in Carnon… This morning, I ran along the canal for about an hour and at last saw some pink flamingos close enough to take pictures (if only to convince my daughter that there were flamingos in the area!). Then I ... [Read more...]

I fought with my LαTεX compiler this morning as it did not want to deal with my code: looking on forums for incompatibilities between beamer and algorithmic, and adding all kinds of packages, to no avail. Until I realised one \STATE was missing: (This is connected with my ... [Read more...]

A few more comments on the specific entry on ABC written by Mikael Sunnåker et al…. The entry starts with the representation of the posterior probability of an hypothesis, rather than with the posterior density of a model parameter, which seems to lead the novice reader astray. After all, (... [Read more...]

Forestry is the province of variability. From a spatial point of view this variability ranges from within-tree variation (e.g. modeling wood properties) to billions of trees growing in millions of hectares (e.g. forest inventory). From a temporal point of view … Continue reading → [Read more...]

It took us a loooong while [for various and uninteresting reasons] but we finally ended up completing a paper on ABC using empirical likelihood (EL) that was started by me listening to Brunero Liseo’s tutorial in O’Bayes-2011 in Shanghai… Brunero mentioned empirical likelihood as a semi-parametric technique w/... [Read more...]

This post is written by Julien Cornebise. Last week in Aachen was the 3rd Edition of the Bayes(Pharma) workshop. Its specificity: half-and-half industry/academic participants and speakers, all in Pharmaceutical statistics, with a great care to welcome newcomers to Bayes, so as to spread as much as possible the ... [Read more...]

There are quite a few books out now on “data science”. I’ve picked out three that I think are the best place to start for computational journalists. First is Machine Learning for Hackers, by Drew Conway and John Myles White. The autho... [Read more...]

I spent most of the Sunday afternoon trying to understand why defining did not have the same effect as writing the line until I found there is a clash due to the comment package… The assuredly simple code produces an error message: This is quite an inconvenience as I need ... [Read more...]

On Tuesday, Eric Chi and Kenneth Lange arXived a paper on a comparison of numerical techniques for solving sudokus. (The very Kenneth Lange who wrote this fantastic book on numerical analysis.) One of these techniques is the simulated annealing approach I had played with a long while ago.  They seem ... [Read more...]

I was grading my Master projects this morning and came upon this graph: which compares the variability of an importance-sampling estimator versus its self-normalised alternative… This is an interesting case in that self-normalisation does considerably degrade the quality of the approximation in that setting. In other cases, self-normalisation may bring ... [Read more...]

Large-scale Inference by Brad Efron is the first IMS Monograph in this new series, coordinated by David Cox and published by Cambridge University Press. Since I read this book immediately after Cox’ and Donnelly’s Principles of Applied Statistics, I was thinking of drawing a parallel between the two books. ... [Read more...]