[Thanks for dropping by, Hacker News readers! If you want to see more about what R can do, check out these posts on using R to create calendar heat maps, or to do live social network analysis on Twitter. You can run the code in REvolution R.]
In an article at Information Management, Steve Miller casts an analyst's eye at the future of R in the commercial analytic software market currently dominated by SAS and the recently-acquired SPSS. He discusses the recent round of venture funding here at REvolution, and identifies innovation as one of the reasons why there is so much momentum behind R recently:
REvolution inherits much goodwill as the commercial vendor of R. R's meteoric rise in academic and research worlds is nothing short of remarkable. Even with an estimated 2M worldwide users currently, R's popularity continues to rise. And with an easily extensible object-oriented architecture and so many zealous users, it's little wonder that R laps the competitive field incorporating the latest statistical techniques. R innovation is quite astonishing, testimony to the power of the open source software model. The number of freely-available packages developed by the R community is approaching 2000. Take a look at the accessible R machine learning modules. Now check how many of these techniques are implemented in other statistical platforms.
But how can R have an impact beyond academia and research into the commercial world? It's through graduates, says Miller:
In 2009, the statistical platform of choice at top graduate schools around the world is R, not SAS. And like their SAS brethren of 25 years ago, as they enter the work world, these new statisticians wish to continue using what they've learned and love -- only now it's R. This transition from SAS to R in academy is, I believe, a leading indicator of change in the statistical marketplace 5 to 10 years out.
Information Management: Statistical Revolution
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