My friends Randal Douc and Éric Moulines just published this new time series book with David Stoffer. (David also wrote Time Series Analysis and its Applications with Robert Shumway a year ago.) The books reflects well on the research of Randal and Éric over the past decade, namely convergence results on Markov chains for validating both inference in nonlinear time series and algorithms applied to those objects. The later includes MCMC, pMCMC, sequential Monte Carlo, particle filters, and the EM algorithm. While I am too close to the authors to write a balanced review for CHANCE (the book is under review by another researcher, before you ask!), I think this is an important book that reflects the state of the art in the rigorous study of those models. Obviously, the mathematical rigour advocated by the authors makes Nonlinear Time Series a rather advanced book (despite the authors’ reassuring statement that “nothing excessively deep is used”) more adequate for PhD students and researchers than starting graduates (and definitely not advised for self-study), but the availability of the R code (on the highly personal page of David Stoffer) comes to balance the mathematical bent of the book in the first and third parts. A great reference book!
Archive for Eric Moulines
Congratulations to my friend Éric Moulines who just received the Silver medal from the national scientific research centre CNRS for the Institut des sciences de l’ingénierie et des systèmes (INSIS). Besides conducting top edge research in a wide spectrum of topics in statistics, probability and signal processing, including his influential book on Hidden Markov Models with Olivier Cappé and Tobias Rydén, (a paperback version is now available!) he has been intensely involved in driving national research policy for many years. This (prestigious) reward is thus well-deserved! (Congratulations to Alice Guionnet, too, for her Silver medal for the Institut national des sciences mathématiques et de leurs interactions (INSMI)!)