CRAN does not validate R packages!

A friend called me the other day for advice on how to submit an R package to CRAN along with a proof his method was mathematically sound. I replied with some items of advice taken from my (limited) experience with submitting packages. And with the remark that CRAN would not validate the mathematical contents of the associated package manual. Nor even the validity of the R code towards delivering the right outcome as stated in the manual. This shocked him quite seriously as he thought having a package accepted by CRAN was a stamp of validation of both the method and the R code. It would be nice of course but would require so much manpower that it seems unrealistic. Some middle ground is to aim at a journal or a peer community validation where both code and methods are vetted. Which happens for instance with the Journal of Computational and Graphical Statistics. Or the Journal of Statistical Software (which should revise its instructions to authors that states “The majority of software published in JSS is written in S, MATLAB, SAS/IML, C++, or Java”. S, really?!)

As for the validity of the latest release of R (currently R-3.6.1 which came out on 2019-07-05, named Action of the Toes!), I figure the bazillion R programs currently running should be able to detect any defect pretty fast, although awareness of the incredible failure of sample() reported in an earlier post took a while to appear.

essential cover!

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…

packed off!!!

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!!!

local package delays

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!