![ABC model choice via random forests [and no fire]](https://xianblog.files.wordpress.com/2012/04/dscn2914.jpg?w=254&h=452)
While my arXiv newspage today had a puzzling entry about modelling UFOs sightings in France, it also broadcast our revision of Reliable ABC model choice via random forests, version that we resubmitted today to Bioinformatics after a quite thorough upgrade, the most dramatic one being the realisation we could also approximate the posterior probability of […]
![R/Rmetrics in Paris [alas!]](http://xianblog.files.wordpress.com/2014/06/bernard1.jpg?w=349&h=466)
Today I gave a talk on Bayesian model choice in a fabulous 13th Century former monastery in the Latin Quarter of Paris… It is the Collège des Bernardins, close to Jussieu and Collège de France, unbelievably hidden to the point I was not aware of its existence despite having studied and worked in Jussieu since […]
![Bayesian Data Analysis [BDA3 - part #2]](http://i2.wp.com/andrewgelman.com/wp-content/uploads/2013/06/Screen-Shot-2013-06-25-at-10.19.59-PM.png?resize=507%2C652)
Here is the second part of my review of Gelman et al.’ Bayesian Data Analysis (third edition): “When an iterative simulation algorithm is “tuned” (…) the iterations will not in general converge to the target distribution.” (p.297) Part III covers advanced computation, obviously including MCMC but also model approximations like variational Bayes and expectation propagation […]
Andrew Gelman and his coauthors, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin, have now published the latest edition of their book Bayesian Data Analysis. David and Aki are newcomers to the authors’ list, with an extended section on non-linear and non-parametric models. I have been asked by Sam Behseta to write […]
![MCMSki IV [day 3]](http://xianblog.files.wordpress.com/2014/01/ridge5.jpg?w=450&h=302)
Already on the final day..! And still this frustration in being unable to attend three sessions at once… Andrew Gelman started the day with a non-computational talk that broached on themes that are familiar to readers of his blog, on the misuse of significance tests and on recommendations for better practice. I then picked the […]
I just updated my short review on Bayesian computational tools I first wrote in April for the Annual Review of Statistics and Its Applications. The coverage is quite restricted, as I took advantage of two phantom papers I had started a while ago, one with Jean-Michel Marin, on hierarchical Bayes methods and on ABC. (As […]
We have now completed our revision of the paper Relevant statistics for Bayesian model choice, written with Judith Rousseau, Jean-Michel Marin, and Natesh Pillai. It has been resubmitted to Series B and reposted on arXiv. The major change in the paper is the inclusion of a check about the relevance of a given summary statistics, [...]
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. However, while none of them can [...]
