There seems to be a cathaRsis taking place.
My story published Tuesday on the R programming language has generated a flood of reader e-mail messages. The story covers the software’s broad usage and vibrant developer community in detail, but, in short, R helps people deal with large volumes of data in a wide variety of industries, including pharmaceuticals, finance and oil and gas.
Also of note, the software is open source, meaning people can pick it up for free and make their own changes to the code. Such flexibility has inspired statistically minded people of all stripes to get behind R and make it a real success story.
Most of the people reacting to the story expressed pleasure at seeing R receive mainstream attention. People chimed in with the unique ways they’re using the technology. Vhayu Technologies talked about its passion for tweaking R to help traders on Wall Street, while others discussed its increasing adoption at universities for everything from biology to economics.
There were also some complaints that my story did not focus enough on S, which was a precursor to R developed at Bell Labs. John Chambers, now a consulting professor of statistics at Stanford University, drove much of the early S work at Bell Labs and talked with me at length about S and R. Without question, R arrived as a result of the fine work done with S, but it’s the rapid rise of R, helped by its open-source nature, that has proved so gripping.
Speaking of R, Mr. Chambers said, “It’s way beyond anything we could have imagined at Bell Labs.”
If you’d like some more of S’s history, you’ll find it at the end of Mr. Chambers’s new book, “Software for Data Analysis.”
In addition, the commercial potential of R is worth some further discussion.
Pfizer was a prominent R user mentioned in the story. The company relies on R for its nonclinical drug studies and has shied away from using the technology for clinical research that will ultimately be presented to regulators. For such work, Pfizer instead turns to software from SAS Institute, which brings in more than $2 billion a year in revenue from data analytics software and services.
Were Pfizer to use R in clinical studies, it would run the risk of seeing its research questioned or even rejected by regulators doubting the veracity of results based on what they view as an unknown quantity.
“It’s very hard to displace the industry standard in those types of cases,” said Max Kuhn, associate director of nonclinical statistics at Pfizer.
Of course, the Linux operating system over the course of many years has managed to rise from an unknown entity to one that has gained top approval from governments around the world for everything from handling top-secret files to being used for processing tax data. So we’ll see what happens with R in the long run.
Revolution Computing stands as one company trying to push the commercial agenda forward with R.
While the base software is free, Revolution offers ways to speed up the software on certain applications and to run it on large computers. In addition, Revolution provides support services to customers like Pfizer and Bank of America. Intel’s venture capital arm invested in Revolution last year.
Lastly, some readers had questions on exactly how many people use R. A number of people interviewed, including those who work most closely with the software, estimated the R population at 250,000.
Intel Capital has placed the number of R users at 1 million, and Revolution kicks the estimate all the way up to 2 million.
Such disparity often accompanies open-source projects, where it’s difficult to tell just how far a piece of software’s tentacles spread and how active the users really, um, R.
Articulo original aquí.