R 3.0.0 Released

DaBombDotCom writes "R, a popular software environment for statistical computing and graphics, version 3.0.0 codename "Masked Marvel" was released. From the announcement: 'Major R releases have not previously marked great landslides in terms of new features. Rather, they represent that the codebase has developed to a new level of maturity. This is not going to be an exception to the rule. Version 3.0.0, as of this writing, contains only [one] really major new feature: The inclusion of long vectors (containing more than 2^31-1 elements!). More changes are likely to make it into the final release, but the main reason for having it as a new major release is that R over the last 8.5 years has reached a new level: we now have 64 bit support on all platforms, support for parallel processing, the Matrix package, and much more.'"

Comments

Congratulations R Team

[Anonymous Coward]

Someone who can't afford license fee of SAS or Matlab, this is the best alternative out there. And in some cases a better alternative.

Not well known but R's accessibility support is far better. Here is an example from a paper accepted in R Journal

Statistical Software from a Blind Person's Perspective
A. Jonathan R. Godfrey

http://journal.r-project.org/accepted/2012-14/Godfrey.pdf

Re:Congratulations R Team

[Anonymous Coward]

It also feels more appropriate, somehow, to do research code in R: It's supposed to be shareable and reproducible, and using an expensive and proprietary language kind of defeats the purpose. Besides, CRAN and Bioconductor have rather a lot of useful stuff...

Re:Congratulations R Team

[Bill_the_Engineer]

Tell that to all the "scientists" and "researchers" paying money for _and_ investing lifetimes worth of effort into writing libraries for Matlab, Maple, Mathematica, LabView and other proprietary environments, instead of contributing to make the existing free environments better.

Times are changing. There are many forces at work here:

1. Cutbacks in funding is making lead scientists look for ways to save money.
2. The proprietary vendors upgrading their software and charging license fees for each version (one particular vendor licenses specific minor versions).
3. The desire to share work and non-proprietary methods are the best way to do it.
4. New postdocs are familiar with python (they like working in iPython in particular) and its libraries.
5. R is gaining ground with the older scientists due to its features and price.