The "R" Statistical Environment, and REvolution Computing, Spread Out
As we noted in this post, one of the open source-focused companies that made a big splash at the recent OSCON conference was REvolution Computing. The company champions the use of R, an open source language and environment for statistical computing and graphics. R is used by many researchers when parallel processing of statistical data can help sift and analyze large amounts of information. We discussed what it's capable of at length in this post, and here are some of the new directions REvolution Computing and R are going in.
REvolution Computing offers REvolution R, an enhanced distribution of R, as a free download. It also offers REvolution R Enterprise, a subscription-based version of R aimed at large companies that work with large data sets, and ParallelR (included in the Enterprise edition), which can take advantage of multi-processor systems and clusters for large data crunching tasks. R itself, and REvolution's versions, are being embraced in a number of fields, with a number of innovative new applications arriving.
You can view sample applications and read about how R is being applied in financial applications here. "REvolution R is a powerful platform for rapidly solving problems in quantitative finance, econometrics and risk analysis," says REvolution's post. REvolution R is also being widely used in Life Sciences applications, as discussed here. Bioinformatics, Pharmacometrics and Biostatistics are all fields where R is picking up adoption.
Danese Cooper works on R-related tasks for REvolution Computing, and O'Reilly Radar recently interviewed her about how R is spreading out. She notes in the interview that R may play a role in helping the Obama administration move government systems to open source solutions, and she notes that Wolfram Alpha contains parts of R in its statistical data-crunching algorithms. She also notes this:
"We know that R gets used all the time, like by the New York Times, by people who show quantitative data in the popular media...And I was quite surprised to discover recently in the predictive analytics world that Google, LinkedIn, and Facebook all use R to do really exotic things like predict user behavior...We know how to run our product on the cloud in EC2 and other cloud-related things. We're seeing mash-ups where there was a recently a paper where somebody was mashing R with Hadoop."
Her interview is worth reading, and if R or REvolution Computing's offerings are of interest to you, take a look at our post from last year. It includes items of interest on how R can be married to relational databases, and several readers wrote in with adjunct and alternative open source projects focused on statistics.