A chance occurrence on X validated: a question on an incomprehensible formula for Bayesian model choice: which, most unfortunately!, appeared in Bayesian Essentials with R! Eeech! It looks like one line in our LATEX file got erased and the likelihood part in the denominator altogether vanished. Apologies to all readers confused by this nonsensical formula!
Archive for Bayesian Core
[A review of Bayesian Essentials that appeared in Technometrics two weeks ago, with the first author being rechristened Jean-Michael!]
“Overall this book is a very helpful and useful introduction to Bayesian methods of data analysis. I found the use of R, the code in the book, and the companion R package, bayess, to be helpful to those who want to begin using Bayesian methods in data analysis. One topic that I would like to see added is the use of Bayesian methods in change point problems, a topic that we found useful in a recent article and which could be added to the time series chapter. Overall this is a solid book and well worth considering by its intended audience.”
David E. BOOTH
Kent State University
The solution manual to our Bayesian Essentials with R has just been arXived. If I link this completion with the publication date of the book itself, it sure took an unreasonable time to come out and sadly with no obvious reason or even less justification for the delay… Given the large overlap with the solution manual of the previous edition, Bayesian Core, this version should have been completed much much earlier but, paradoxically if in-line with the lengthy completion of the book istelf, this previous manual is one of the causes for the delay, as we thought the overlap allowed for self-study readers to check some of the exercises. Prodded by Hannah Bracken from Springer-Verlag, and unable to hire an assistant towards this task, I eventually decided to spend the few days required to clean up this solution manual, with the unintentional help from my sorry excuse for an Internet provider who accidentally cutting my home connection for a whole week so far…!
In the course of writing solutions, I stumbled upon one inexplicably worded exercise about the Lemer-Schur algorithm for testing stationarity, exercise that I had to rewrite from scratch. Apologies to any reader of Bayesian Essentials with R getting stuck on that exercise!!!
Our book is nearly out..! The Springer webpage is ready, we have sent the proofs back, amazon
is missing has now included the above picture, things are moving towards the publication date, supposed to be November 30. Just in time for Christmas! And not too early given that we packed off in early February…
Deliverance!!! We have at last completed our book! Bayesian Essentials with R is off my desk! In a final nitty-gritty day of compiling and recompiling the R package bayess and the LaTeX file, we have reached versions that were in par with our expectations. The package has been submitted to CRAN (it has gone back and forth a few times, with requests to lower the computing time in the examples: each example should take less than 10s, then 5s…), then accepted by CRAN, incl. a Windows version, and the book has be sent to Springer-Verlag. This truly is a deliverance for me as this book project has been on my work horizon almost constantly for more than the past two years, led to exciting times in Luminy, Carnon and Berlin, has taken an heavy toll on my collaborations and research activities, and was slowly turning into a unsavoury chore! I am thus delighted Jean-Michel and I managed to close the door before any disastrous consequence on either the book or our friendship could develop. Bayesian Essentials with R is certainly an improvement compared with Bayesian Core, primarily by providing a direct access to the R code. We dearly hope it will attract a wider readership by reducing the mathematical requirements (even though some parts are still too involved for most undergraduates) and we will keep testing it with our own students in Montpellier and Paris over the coming months. In the meanwhile, I just enjoy this feeling of renewed freedom!!!
When Jean-Michel and I left Berlin, a month ago, I really thought we were that close to sending the new edition of Bayesian Core. Alas, we are not done yet for a series of reasons: leaving for India did not give me enough time to complete the help manual, some codes from the original version did not seem to work any longer, apparently jeopardising a whole chapter!, and the package did not seem to compile. Yesterday, we met again and made progress that makes me much more confident. For one thing, the R code that “did not work” was an original spreadsheet of Bayesian Core that we turned into functions towards the completion of the bayess package. However, due to sloppy programming at the time, we had used global variables that were called inside functions without being (explicitly) declared as variables. When those R codes got turned into functions, variables defined inside those functions were no longer global and recognised by the other functions defined within those same functions… Silly me! Once this issue got spotted by Jean-Michel, as well as the use of a few && instead of &’s, the whole problem unravelled rather quickly and we got a compiled package by the end of the day, even though some of the demos (reproducing the outcome found in the text) are still bugged. Stay tuned!