Follow up to R Threatens SAS Story in NYT

[ajayohri]

http://bits.blogs.nytimes.com/2009/01/08/r-you-ready-for-r/

There seems to be a cathaRsis taking place.

My story<http://www.nytimes.com/2009/01/07/technology/business-computing/07program.html>
published
Tuesday on the R programming language <http://www.r-project.org/> 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<http://vhayu.typepad.com/marketdata/2008/07/the-rise-of-r.html>
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<http://books.google.com/books?id=UXneuOIvhEAC&pg=PA31&lpg=PA31&dq=chambers+software+for+data+analysis&source=web&ots=2aqsqP-PxB&sig=8fQSShKEkJfKyEEdhTZwKkjyLqM&hl=en&sa=X&oi=book_result&resnum=2&ct=result>
."

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 <http://www.revolution-computing.com/> 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.

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