R in Industry

To those following this thRead:

There was a thread on this topic a year or so ago on this list, in which
contributors mentioned reasons that corporate powers-that-be were
reluctant to commit to R as a corporate statistical platform.  (My
favorite was "There is no one to sue if something goes wrong.")

One reason that I do not think was discussed then, nor have I seen
discussed since, is the issue of the continuity of support.  If one
person has contributed disproportionately heavily to the development and
maintenance of a package, and then retires or follows other interests,
and the package needs maintenance (perhaps as a consequence of new
operating systems or a new version of R), is there any assurance that it
will be available?  With a commercial package such as, say, SPSS, the
corporate memory and continuance makes such continued maintenance
likely, but is there such a commitment with R packages?  If my company
came to depend heavily on a fairly obscure R package (as we are
contemplating doing), what guarantee is there that it will be available
next month/year/decade?  I know of none, nor would I expect one.

As R says when it starts up, "R is free software and comes with
ABSOLUTELY NO WARRANTY."

Ben Fairbank


-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Patrick Burns
Sent: Thursday, February 08, 2007 10:24 AM
To: Albrecht,Dr. Stefan (AZ Private Equity Partner)
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] R in Industry

 From what I know Matlab is much more popular in
fixed income than R, but R is vastly more popular in
equities.  R seems to be making quite a lot of headway
in finance, even in fixed income to some degree.

At least to some extent, this is probably logical behavior --
fixed income is more mathematical, and equities is more
statistical.

Matlab is easier to learn mainly because it has much simpler
data structures.  However, once you are doing something
where a complex data structure is natural, then R is going to
be easier to use and you are likely to have a more complete
implementation of what you want.

If speed becomes a limiting factor, then moving the heavy
computing to C is a natural thing to do, and very easy with R.

Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and "A Guide for the Unwilling S User")

Albrecht, Dr. Stefan (AZ Private Equity Partner) wrote:

Dear all,

I was reading with great interest your comments about the use of R in
the industry. Personally, I use R as scripting language in the

financial

industry, not so much for its statistical capabilities (which are
great), but more for programming. I once switched from S-Plus to R,
because I liked R more, it had a better and easier to use documentation
and it is faster (especially with loops).

Now some colleagues of mine are (finally) eager to join me in my
quantitative efforts, but they feel that they are more at ease with
Matlab. I can understand this. Matlab has a real IDE with symbolic
debugger, integrated editor and profiling, etc. The help files are
great, very comprehensive and coherent. It also could be easier to
learn.

And, I was very astonished to realise, Matlab is very, very much faster
with simple "for" loops, which would speed up simulations considerably.
So I have trouble to argue for a use of R (which I like) instead of
Matlab. The price of Matlab is high, but certainly not prohibitive. R

is

great and free, but maybe less comfortable to use than Matlab.

Finally, after all, I have the impression that in many job offerings in
the financial industry R is much less often mentioned than Matlab.

I would very much appreciate any comments on my above remarks. I know
there has been some discussions of R vs. Matlab on R-help, but these
could be somewhat out-dated, since both languages are evolving quite
quickly.

With many thanks and best regards,
Stefan Albrecht



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