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Date:         Wed, 7 Jan 2009 12:14:43 -0500
Reply-To:     "Hixon, John" <jhixon@AMGEN.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         "Hixon, John" <jhixon@AMGEN.COM>
Subject:      Re: R "Threatens" SAS, According to The New York Times
Comments: To: "msz03@ALBANY.EDU" <msz03@ALBANY.EDU>
Comments: cc: "jhixon2@cox.net" <jhixon2@cox.net>,
          John Hixon <john_hixon@mail.uri.edu>
Content-Type: text/plain; charset="us-ascii"

Hello Mike and all SAS-L'rs.

I saw the article about R in this morning's NYTimes.

I found it quite a coincidence that one of the people quoted was Max Kuhn at Pfizer, since yesterday evening I loaded his R-package named 'caret' onto my "school" laptop.

I've enrolled (part-time) in an Interdisciplinary PhD program in Applied Mathematical Sciences with a concentration in Biophysics/Bioinformatics at URI. For my first class, I signed up for Bioinformatics I, but I withdrew after one class (and took a different required course).

Why did I withdraw? After scanning the Bioinformatics textbook, and doing some web research, it became clear that I would need to learn R (at a minimum) and perhaps also Python, in order to take advantage of the current tools available for Bioinformatics.

It is very clear that the latest statistical methods will always appear first as R packages, since there is a multitude of PhD statisticians using and extending the software.

I am a member of ASA. I subscribe to the Journal of Computational and Graphical Statistics. At the end of each issue there is a section titled "Recent Publications in JSS" [Journal of Statistical Software]. 98% of the references are to new packages written for R.

As part of a project in my most recent URI class, I needed to use Kernel-based Support Vector Machines (KSVM) as a classification method. I e-mailed a few contacts I have at SAS to inquire whether there were any IML subroutines that implemented SVM methods in SAS. The answer was: if there are any SAS methods for SVMs they would probably be in Enterprise Miner (which of course no one can afford).

But, kernel SVMs are readily available in R (for example see the R package 'kernlab').

I am in the very early days of gaining some R expertise, but, I am excited by what I find. It seems to be 'the place to be' if you want to be current with the latest statistical methods.

That being said, I work for Amgen in a heavily regulated industry (FDA, EMEA). For Amgen work, I only use SAS, since I wonder about whether we can consider R package "XYZ" from Professor "ABC", to be 'validated', (as we can with the PROCS in SAS).

Still, for my schoolwork, I intend to do all required analyses "both ways": using both SAS and R, so that I can become more proficient with R. Of course, that only applies to the analyses that are *possible* in SAS (using SAS/STAT SAS/IML, SAS/OR etc. which are licensed by URI). I have already run into the situation where I can do analyses in R that are not possible for me in SAS.

If I worked at SAS, that would frighten me.

To get some notion of the depth of packages available in R, have a look at this recent JSS paper written by Max Kuhn. You can view it here:

http://www.jstatsoft.org/v28/i05/paper

Notice in particular, Table 1 on Page 9. This shows only a subset of the model-building methods available in R. Only a subset of these methods are available in SAS STAT/IML etc. I assume that others are available in SAS Enterpise Miner, but I have never been exposed to that SAS module since neither of my previous employers could afford the immense cost.

So..my message to young statisticians is : learn *both* SAS and R.

I have always *loved* writing SAS code. I enjoy the creativity of using SAS to develop applications that automate the analysis and graphical presentation of complex data streams. I will always love SAS.

But...a young lovely named R has caught my attention of late, and, she's quite seductive with her manifold charms, (and she seems to grow even more seductive as she matures...)

:-)

For example: try googling: rggobi or bioconductor....

Cheers,

John Hixon

jhixon@amgen.com john_hixon@mail.uri.edu jhixon2@cox.net

>Date: Wed, 7 Jan 2009 08:53:55 -0500 >From: Mike Zdeb <msz03@ALBANY.EDU> >Subject: Re: R "Threatens" SAS, According to The New York Times

>hi ... neat read in that we have a bit of the same debate here (though it's heavily SAS-weighted)

>noticed the quote from the person at Pfizer re R in the Times article

>also noticed the job posting for Pfizer's "Associate Director/ Director, Quantitative Epidemiologist" at

>http://www.icrunchdata.com/ViewJob.aspx?id=7354&keys=sas

>that includes no mention of proficiency with R, but does include ...

>Responsibilities ><yadda yadda yadda> >"Hands on involvement in epidemiological projects including use of epidemiology databases, SAS programming, quality control checks for programs, and documentation" >"Knowledge of SQL and automated programming including SAS macros and interface development"

>Qualifications ><blah blah blah> >"Proficiency in SAS programming, including statistical analysis procedures, and experience with other statistical software"

>I guess that R would fall into that large "OTHER STATISTICAL SOFTWARE" vat

>-- >Mike Zdeb >U@Albany School of Public Health >One University Place >Rensselaer, New York 12144-3456 >P/518-402-6479 F/630-604-1475

> On Tue, 6 Jan 2009 20:41:40 -0800, Virtual SUG <sfbay0001@AOL.COM> wrote: > >>Hello everyone... >> >>Thought you might be interested in reading this article, which appears >>in the 1/6/9 online edition of The New York Times: >> >>http://www.nytimes.com/2009/01/07/technology/business- > computing/07program.html >> >>The headline is "Data Analysts Captivated by R's Power," and towards >>the end of the story is the following paragraph: >> >>"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. " >> >>Andrew Karp >>Sierra Information Services >>www.SierraInfomation.com > > > Even David and Toby were implicitly mentioned in the article: > > "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." > > pax, > Ken Borowiak > >


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