“The R-Files” is an occasional series from Revolution Analytics, where we profile prominent members of the R Community.
Name: Dirk Eddelbuettel
Background: Ph.D. (EHESS, France), Quantitative Analyst
Years Using R: About 15
Known for: RQuantlib, Rcpp/RInside, R packaging for Debian/Ubuntu, Task
Dirk Eddelbuettel is an active member of the R community who has been contributing packages to CRAN for nearly a decade. An early adopter of Linux, he was first introduced to R in 1996. “The world was smaller then–much of the open source community were reading the same mailing lists and news groups at the time,” he said. “I had known about S for several years, and was starting to use S+ in my first job out of graduate school. So when I learned about R, there was a natural curiosity about this implementation and what it could do as a next step for data analysis.”
Eddelbuettel is also an early contributor to the Debian project, where he got in contact with Doug Bates. It was Bates, who was already a long-time S user and R Core contributor himself, who helped Eddelbuettel with some early steps in R. He became increasingly interested in R, started to co-maintain it in Debian with Bates, and began to use it for more and more projects. Since he already had a background with S, he was not as affected by the learning curve that can come with R and was soon actively developing packages.
To date, Eddelbuettel has authored or co-authored well over a dozen packages in CRAN, including RQuantLib (an R interface to the QuantLib libraries), digest, RDieHarder, and the popular Rcpp (C++ classes for extending R with C/C++ functions, which is now co-authored with Romain Francois counting on frequent contribution by Bates and John Chambers) and RInside (for embedding R in C++ applications, now also co-authored with Romain Francois). He has also been a contributor to other R-Forge projects including phylobase, inline and blotter. He is editor of the CRAN Task Views for Finance as well as High-Performance Computing, and serves as an editor at the Journal of Statistical Software.
When asked about what draws him to R, Eddelbuettel echoes a common sentiment. “Behind R stands an exceptional community that’s comprised of many of the world’s brightest, savviest statistical minds. I get so much out of R and I'm happy to be able to contribute a little bit back, be in the form of new packages or the Debian packaging.” He adds, “While I do use R during my day job, it's also a hobby of mine. I build packages that I think solve interesting problems and hopefully benefit the community, and I know that there are many others out there with the same mindset, doing the same thing.”
Looking to the future, Eddelbuettel acknowledges that it's difficult to predict new developments for R, given that it's driven by a diverse community with a multitude of interests and pursuits. “It's hard to speculate where R will go in the next few years–it's not like there's any official governing body. If you want to see something new in R, do it. That's the inherent beauty of R: it's driven by both the R Core group and the the community at large –especially the researchers and developers that continue to innovate and introduce new things to R.”