This paper proposes a new approach to likelihood-free model choice based on random forest classifiers. These are fit to

Second day at the Indo-French Centre for Applied Mathematics and the workshop. Maybe not the most exciting day in terms of talks (as I missed the first two plenary sessions by (a) oversleeping and (b) running across the campus!). However I had a neat talk with another conference participant that led to

While working with Andrew and a student from Dauphine on importance sampling, we wanted to assess the distribution of the resulting sample via the Kolmogorov-Smirnov measure where F is the target. This distance (times √n) has an asymptotic distribution that does not depend on n, called the Kolmogorov distribution. After searching for a little while,

As promised, I got back to this book, Implementing reproducible research (after the pigeons had their say). I looked at it this morning while monitoring my students taking their last-chance R exam (definitely last chance as my undergraduate R course is not reconoduced next year). The book is in fact an edited collection of papers

Here are our slides for the ABC short course Jean-Michel and I give at ISBA 2014 in Cancún next Monday (if your browser can manage Slideshare…) Although I may switch the pictures from Iceland to Mexico, on Sunday, there will be not much change on those slides we both have previously used in previous

When is R Slow, and Why? Computational speed is a common complaint lodged against R. Some recent posts on r-bloggers.com have compared the speed of R with some other programming languages , and showed the favorable impact of the new compiler package on run-times . I and others have written about using Rcpp to easily write C++...

Following yesterday’s post on Rao’s, Liu’s, and Dunson’s paper on a new approach to intractable normalising constants, and taking advantage of being in Warwick, I tested the method on a toy model, namely the posterior associated with n Student’s t observations with unknown location parameter μ and a flat prior, which is “naturally” bounded by

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

After more than a year of collaboration, meetings, simulations, delays, switches, visits, more delays, more simulations, discussions, and a final marathon wrapping day last Friday, Jean-Michel Marin, Pierre Pudlo, and I at last completed our latest collaboration on ABC, with the central arguments that (a) using random forests is a good tool for choosing the