R in the NY Times

I've detailed, R, that wonderful piece of statistical software in a previous post, but an article in today's NY Times gives some nice additional background to the whole project. Check it out if you want to know "the rest of the story." There's also a delightfully snarky quote from a spokesperson for SAS, the chief commercial rival to R.

“I think it addresses a niche market for high-end data analysts that want free, readily available code," said Anne H. Milley, director of technology product marketing at SAS. She adds, “We have customers who build engines for aircraft. I am happy they are not using freeware when I get on a jet.”

Because everyone knows that commercial software is always reliable. Personally, I don't care what software an engineer uses to design a jet. Just as long as the software and the engineer both know what they're doing. The same goes for the software (a mix of commercial, open source, and free closed-source programs) I use in my own research--I'm not a complete open source zealot (all my FEA analyses are on commercial software, because I still haven't found an open source alternative that doesn't require a computer science degree), but if I can get the job done for free, the price is right!

Thanks to Denim and Tweed for pointing me towards this link.

The Open Source Dissertation

My university has done a wonderful thing, in accepting only PDF files for deposition of a thesis or dissertation with the graduate school. Gone are the days of printing 5 copies of a 300-page document on acid-free paper that costs 20 cents a page (and then finding out that one of the margins is 0.1" too wide, so please correct and resubmit before the deadline in three hours). The transition is a wonderful step forward, and also means that it is much easier to distribute the dissertation.

As a proponent of free and open source software (having made the big switch about a year ago), I wanted to do as much as I could within the realms of that universe. This posting summarizes the software I used, with the hope of inspiring others to follow a similar path (whether in whole or in part).

Data visualization: I processed all of my CT scan data in 3D Slicer. For segmenting structures, generating surfaces, and measuring volumes, look no further! [I still need to do a more complete post on this one.] Additional analysis was done in ImageJ.

Data analysis: Initial data entry in OpenOffice.org's Calc, with analysis primarily in R and an occasional venture to PAST.

Figures: Raster image editing was done in the GIMP, and line drawings or composite figures were assembled in Inkscape.

Word processing: All done in OpenOffice.org's Writer. The PDF output function was very nice for sending drafts to committee members and advisors, and the software's Microsoft Office compatibility is such that I could also send and receive marked-up documents (in .doc format) pretty easily. For the final document, I exported each chapter in PDF format.

Referencing: All of my references were sorted, organized, and rendered as bibliographies with Zotero. Along the way, I created custom styles for Journal of Vertebrate Paleontology and Zoological Journal of the Linnean Society. More on this process in another post.

Document assembly: To assemble all of my dissertation's chapters into a single PDF document, I used Ghostscript. The output was quite pleasing, and easily accomplished through the command line in a matter of seconds.

Presentations: For my oral dissertation defense, I created my presentation using OpenOffice.org's Impress.

Update on PAST in Wine

A previous post detailed instructions for running the statistical program PAST within the Linux program Wine, which required turning on the virtual desktop option. Something happened between that post and the last few updates of both PAST (currently at 1.80) and Wine (now at 0.9.59), because now PAST runs just fine without any special options! This means that you can now turn the virtual desktop option back off - this is nice, because it gives you a lot more freedom in terms of resizing, minimizing, and moving the PAST window.

Wow, I think that was possibly the geekiest and most jargon-laden post I've ever written.

R for Paleontologists

Quite by accident, while searching for the answer to another question I had about R (a powerful open source statistical language), I ran across a nice set of PDFs from a short course called, "Data Analysis in Paleontology for R." Gene Hunt, curator of Ostracoda at the Smithsonian, ran this nearly two years ago. The PDFs contain slides on topics ranging from the basics of loading data to running a PCA or correcting for phylogeny. As an added bonus, each includes some short exercises to practice your new-found skills. Click this text to follow the link, and then look under "Resources." The slides are posted as five separate PDFs.

I have now switched to R for nearly all of my statistical analysis needs, and have been immensely satisfied so far. Expect a post on this sometime in the next few weeks (hopefully).