At JSM, John Kimmel gave me a copy of the Handbook of Markov chain Monte Carlo, as I had not (yet?!) received it. This handbook is edited by Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng, all first-class jedis of the MCMC galaxy. I had not had a chance to get a look at the book until now as Jean-Michel Marin took it home for me from Miami, but, as he remarked in giving it back to me last week, the outcome truly is excellent! Of course, authors and editors being friends of mine, the reader may worry about the objectivity of this assessment; however the quality of the contents is clearly there and the book appears as a worthy successor to the tremendous Markov chain Monte Carlo in Practice by Wally Gilks, Sylvia Richardson and David Spiegelhalter. (I can attest to the involvement of the editors from the many rounds of reviews we exchanged about our MCMC history chapter!) The style of the chapters is rather homogeneous and there are a few R codes here and there. So, while I will still stick to our Monte Carlo Statistical Methods book for teaching MCMC to my graduate students next month, I think the book can well be used at a teaching level as well as a reference on the state-of-the-art MCMC technology. Continue reading
Archive for Gaussian state spaces
The “ordinary” meeting of the Royal Statistical Society last Wednesday was a tremendous success! The Read Paper by Rue, Martino and Chopin attracted a large crowd, surely partly thanks to the pre-ordinary meeting organised by the Young Statistician Section, and we are likely to see a nice collection of discussions in JRSS B as a result, if the number of discussions at the meeting can be used as a gauge. While I played my role of seconder by pointing out in my discussion the radical viewpoint of the paper according to which all simulation aspects can be erased, I noticed in a second discussion with Roberto Casarin that the Gaussian approximation to the marginal posterior is quite accurate in the stochastic volatility model. I am also looking forward the written discussion by Omiros Papaspiliopoulos where he points out connections with exact simulation methods and marginal representations such as Chib’s estimate of marginal likelihoods. In conclusion, this is certainly one of the most exciting Read Papers of the past years!!!