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http://www.nytimes.com/2009/01/07/technology/business-computing/07program.htm
l?_r=3

R first appeared in 1996, when the statistics professors Robert Gentleman, 
left, and Ross Ihaka released the code as a free software package.
By ASHLEE VANCE
Published: January 6, 2009 

To some people R is just the 18th letter of the alphabet. To others, it��s 
the rating on racy movies, a measure of an attic��s insulation or what 
pirates in movies say. 

R is also 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 it��s 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. I.B.M., Hewlett-Packard and 
Dell make billions of dollars a year selling servers that run the 
open-source Linux operating system, which competes with Windows from 
Microsoft. Most Web sites are displayed using an open-source application 
called Apache, and companies increasingly rely on the open-source MySQL 
database to store their critical information. Many people view the end 
results of all this technology via the Firefox Web browser, also 
open-source software. 

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 
Microsoft��s Excel spreadsheet software that can help illuminate data 
trends more clearly than is possible by entering information into rows and 
columns. 

What makes R so useful �� and helps explain its quick acceptance �� is that 
statisticians, engineers and scientists can improve the software��s 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 that��s already available, so you��re 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 project. 

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 there��s 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 R��s 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 R��s 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 don��t 
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.��
 
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