library, whatzat???

to be demolished!

bravo, Dr. Robert!!!

Last Friday, our daughter Rachel attended the graduation ceremony for her medical school cohort master graduation. On the Saclay campus next to ENSAE (and so did we!), with nice and short talks by medicine professors and the University President, with a massive (?!) conflict of interest as her own daughter was part of this cohort!  And learned that she will work her first medical internship semester in French Guiana, next month, as part of her choice of a medical specialisation in internal medicine in the French Caribbean departments, over the five next years. Congrats to her and all of her fantastic friends for this massive achievement!!! And [fatherly and a wee bit anxious!] best wishes for this new and exciting period of her life!!! (And concerned thoughts for her female doctor colleagues at the French Institute for Mothers and Children in Kabul, like Dr. Arifa and Dr. Shoranghaize. interviewed in Le Monde the same day.)

analyse des données

Introduction to Sequential Monte Carlo [book review]

[Warning: Due to many CoI, from Nicolas being a former PhD student of mine, to his being a current colleague at CREST, to Omiros being co-deputy-editor for Biometrika, this review will not be part of my CHANCE book reviews.]

My friends Nicolas Chopin and Omiros Papaspiliopoulos wrote in 2020 An Introduction to Sequential Monte Carlo (Springer) that took several years to achieve and which I find remarkably coherent in its unified presentation. Particles filters and more broadly sequential Monte Carlo have expended considerably in the last 25 years and I find it difficult to keep track of the main advances given the expansive and heterogeneous literature. The book is also quite careful in its mathematical treatment of the concepts and, while the Feynman-Kac formalism is somewhat scary, it provides a careful introduction to the sampling techniques relating to state-space models and to their asymptotic validation. As an introduction it does not go to the same depths as Pierre Del Moral’s 2004 book or our 2005 book (Cappé et al.). But it also proposes a unified treatment of the most recent developments, including SMC² and ABC-SMC. There is even a chapter on sequential quasi-Monte Carlo, naturally connected to Mathieu Gerber’s and Nicolas Chopin’s 2015 Read Paper. Another significant feature is the articulation of the practical part around a massive Python package called particles [what else?!]. While the book is intended as a textbook, and has been used as such at ENSAE and in other places, there are only a few exercises per chapter and they are not necessarily manageable (as Exercise 7.1, the unique exercise for the very short Chapter 7.) The style is highly pedagogical, take for instance Chapter 10 on the various particle filters, with a detailed and separate analysis of the input, algorithm, and output of each of these. Examples are only strategically used when comparing methods or illustrating convergence. While the MCMC chapter (Chapter 15) is surprisingly small, it is actually an introducing of the massive chapter on particle MCMC (and a teaser for an incoming Papaspiloulos, Roberts and Tweedie, a slow-cooking dish that has now been baking for quite a while!).