[LINK] R programming language
stephen at melbpc.org.au
stephen at melbpc.org.au
Wed Jan 7 21:32:09 AEDT 2009
Data Analysts Captivated by R Power
By ASHLEE VANCE www.nytimes.com Published: January 6, 2009
. R is the name of a popular programming language used by a growing
number of data analysts inside corporations and academia.
It is becoming their lingua franca partly because data mining has entered
a golden age, whether being used to set ad prices, find new drugs more
quickly or fine-tune financial models. Companies as diverse as Google,
Pfizer, Merck, Bank of America, the InterContinental Hotels Group and
Shell use it.
But R has also quickly found a following because statisticians, engineers
and scientists without computer programming skills find it easy to use.
R is really important to the point that its hard to overvalue it, said
Daryl Pregibon, a research scientist at Google, which uses the software
widely. It allows statisticians to do very intricate and complicated
analyses without knowing the blood and guts of computing systems.
It is also free. R is an open-source program, and its popularity reflects
a shift in the type of software used inside corporations. Open-source
software is free for anyone to use and modify ..
R is similar to other programming languages, like C, Java and Perl, in
that it helps people perform a wide variety of computing tasks by giving
them access to various commands.
For statisticians, however, R is particularly useful because it contains
a number of built-in mechanisms for organizing data, running calculations
on the information and creating graphical representations of data sets.
Some people familiar with R describe it as a supercharged version of
Microsofts Excel spreadsheet software that can help illuminate data
trends more clearly than is possible by entering information into rows
What makes R so useful and helps explain its quick acceptance is that
statisticians, engineers and scientists can improve the softwares code
or write variations for specific tasks. Packages written for R add
advanced algorithms, colored and textured graphs and mining techniques to
dig deeper into databases.
Close to 1,600 different packages reside on just one of the many Web
sites devoted to R, and the number of packages has grown exponentially.
One package, called BiodiversityR, offers a graphical interface aimed at
making calculations of environmental trends easier.
Another package, called Emu, analyzes speech patterns, while GenABEL is
used to study the human genome.
The financial services community has demonstrated a particular affinity
for R; dozens of packages exist for derivatives analysis alone.
The great beauty of R is that you can modify it to do all sorts of
things, said Hal Varian, chief economist at Google. And you have a lot
of prepackaged stuff thats already available, so youre standing on the
shoulders of giants.
R first appeared in 1996, when the statistics professors Ross Ihaka and
Robert Gentleman of the University of Auckland in New Zealand released
the code as a free software package.
According to them, the notion of devising something like R sprang up
during a hallway conversation. They both wanted technology better suited
for their statistics students, who needed to analyze data and produce
graphical models of the information. Most comparable software had been
designed by computer scientists and proved hard to use.
Lacking deep computer science training, the professors considered their
coding efforts more of an academic game than anything else. Nonetheless,
starting in about 1991, they worked on R full time. We were pretty much
inseparable for five or six years, Mr. Gentleman said. One person would
do the typing and one person would do the thinking.
Some statisticians who took an early look at the software considered it
rough around the edges. But despite its shortcomings, R immediately
gained a following with people who saw the possibilities in customizing
the free software.
John M. Chambers, a former Bell Labs researcher who is now a consulting
professor of statistics at Stanford University, was an early champion.
At Bell Labs, Mr. Chambers had helped develop S, another statistics
software project, which was meant to give researchers of all stripes an
accessible data analysis tool. It was, however, not an open-source
The software failed to generate broad interest and ultimately the rights
to S ended up in the hands of Tibco Software. Now R is surpassing what
Mr. Chambers had imagined possible with S.
The diversity and excitement around what all of these people are doing
is great, Mr. Chambers said.
While it is difficult to calculate exactly how many people use R, those
most familiar with the software estimate that close to 250,000 people
work with it regularly.
The popularity of R at universities could threaten SAS Institute, the
privately held business software company that specializes in data
analysis software. SAS, with more than $2 billion in annual revenue, has
been the preferred tool of scholars and corporate managers.
R has really become the second language for people coming out of grad
school now, and theres an amazing amount of code being written for it,
said Max Kuhn, associate director of nonclinical statistics at
Pfizer. You can look on the SAS message boards and see there is a
proportional downturn in traffic.
SAS says it has noticed Rs rising popularity at universities, despite
educational discounts on its own software, but it dismisses the
technology as being of interest to a limited set of people working on
very hard tasks.
I think it addresses a niche market for high-end data analysts that want
free, readily available code," said Anne H. Milley, director of
technology product marketing at SAS. She adds, We have customers who
build engines for aircraft. I am happy they are not using freeware when I
get on a jet.
But while SAS plays down Rs corporate appeal, companies like Google and
Pfizer say they use the software for just about anything they can.
Google, for example, taps R for help understanding trends in ad pricing
and for illuminating patterns in the search data it collects. Pfizer has
created customized packages for R to let its scientists manipulate their
own data during nonclinical drug studies rather than send the information
off to a statistician.
The co-creators of R express satisfaction that such companies profit from
the fruits of their labor and that of hundreds of volunteers.
Mr. Ihaka continues to teach statistics at the University of Auckland and
wants to create more advanced software. Mr. Gentleman is applying R-based
software, called Bioconductor, in work he is doing on computational
biology at the Fred Hutchinson Cancer Research Center in Seattle.
R is a real demonstration of the power of collaboration, and I dont
think you could construct something like this any other way, Mr. Ihaka
said. We could have chosen to be commercial, and we would have sold five
copies of the software.
» A version of this article appeared in print on January 7, 2009, on page
B6 of the New York edition.
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