published in Brazilian Journal of Probability and Statistics, esplêndido!

Our paper “Bayesian computation for statistical models with intractable normalizing constants” written with Yves Atchadé and Nicolas Lartillot has now appeared in the Brazilian Journal of Probability and Statistics! (This is my first paper in this journal.) Although we could have used ABC steps to approximate the posterior, we chose instead a Wang-Landau approach that has exact convergence properties and extends the 1992 Read Paper by Charlie Geyer and Elisabeth Thompson.

Bayes by the Bay

No, no, this is not an announcement for a meeting on an Australian beach (which is Bayes on the Beach, taking place next November (6-8) on the Sunshine Coast and is organised by Kerrie Mengersen’s BRAG, at QUT, that I just left! With Robert Wolpert as the international keynote speaker and Matt Wand as the Australian keynote speaker.) Bayes by the Bay is “a pedagogical workshop on Bayesian methods in Science” organised by the Institute of Mathematical Sciences, based in the CIT campus in Chennai. It is taking place on January 4-8, 2013, in Pondichéry. (To use the French spelling of this former comptoir of French India…) Just prior to the ISBA Varanasi meeting on Bayesian Statistics.

Great: the webpage for the workshop uses the attached picture of Pierre-Simon (de) Laplace, rather than the unlikely picture of Thomas Bayes found all over the place (incl. this blog!). This was also the case in Christensen et al.’s Bayesian ideas and data analysis. So maybe there is a trend there. I also like the name “Bayes by the Bay“, as it reminds me of a kid song we used to sing to/with our kids when they were young, “down by the bay“, after a summer vacation with Anne and George Casella…

Coincidentally, my re-read of Laplace’s Théorie Analytique des Probabilitiés just appeared (in English) in the Boletim ISBrA, the dynamic Brazilian branch of ISBA.

Théorie analytique des probabilités

The Brazilian society for Bayesian Analysis (ISBrA, whose annual meeting is taking place at this very time!) asked me to write a review on Pierre Simon Laplace’s book, Théorie Analytique des Probabilités, a book that was initially published in 1812, exactly two centuries ago. I promptly accepted this request as (a) I had never looked at this book and so this provided me with a perfect opportunity to do so, (b) while in Vancouver, Julien Cornebise had bought for me a 1967 reproduction of the 1812 edition,  (c) I was curious to see how much of the book had permeated modern probability and statistics or, conversely, how much of Laplace’s perspective was still understandable by modern day standards. (Note that the link on the book leads to a free version of the 1814, not 1812, edition of the book, as free as the kindle version on amazon.)

“Je m’attache surtout, à déterminer la probabilité des causes et des résultats indiqués par événemens considérés en grand nombre.” P.S. Laplace, Théorie Analytique des Probabilités, page 3

First, I must acknowledge I found the book rather difficult to read and this for several reasons: (a) as is the case for books from older times, the ratio text-to-formulae is very high, with an inconvenient typography and page layout (ar least for actual standards), so speed-reading is impossible; (b) the themes offered in succession are often abruptly brought and uncorrelated with the previous ones; (c) the mathematical notations are 18th-century, so sums are indicated by S, exponentials by c, and so on, which again slows down reading and understanding; (d) for all of the above reasons, I often missed the big picture and got mired into technical details until they made sense or I gave up; (e) I never quite understood whether or not Laplace was interested in the analytics like generating functions only to provide precise numerical approximations or for their own sake. Hence a form of disappointment by the end of the book, most likely due to my insufficient investment in the project (on which I mostly spent an Amsterdam/Calgary flight and jet-lagged nights at BIRS…), even though I got excited by finding the bits and pieces about Bayesian estimation and testing.