[R] Reasons to Use R

[bogdan romocea]

> (1)Institutions (not only academia) using R

http://www.r-project.org/useR-2006/participants.html

> (2)Hardware requirements, possibly benchmarks

Since you mention huge data sets, GNU/Linux running on 64-bit machines
with as much RAM as your budget allows.

> (3)R & clusters, R & multiple CPU machines,
> R performance on different hardware.

OpenMosix, Quantian for clusters; the archive for multiple CPUs (this
was asked quite a few times). It may be best to measure R performance
on different hardware by yourself, using your own data and code.

> (4)finally, a list of the advantages for using R over
> commercial statistical packages.

I'd say it's not R vs. commercial packages, but S vs. the rest of the
world. Check http://www.insightful.com/ , much of what they say is
applicable to R. Make the case that S is vastly superior directly, not
just through a list of reasons: take a few data sets and show how they
can be analyzed with S compared to other choices. Both R and S-Plus
are likely to significantly outperform most other software, depending
on the kind of work that needs to be done.


> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Lorenzo Isella
> Sent: Thursday, April 05, 2007 11:02 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Reasons to Use R
>
> Dear All,
> The institute I work for is organizing an internal workshop for High
> Performance Computing (HPC).
> I am planning to attend it and talk a bit about fluid dynamics, but
> there is also quite a lot of interest devoted to data post-processing
> and management of huge data sets.
> A lot of people are interested in image processing/pattern recognition
> and statistic applied to geography/ecology, but I would like not to
> post this on too many lists.
> The final aim of the workshop is  understanding hardware requirements
> and drafting a list of the equipment we would like to buy. I think
> this could be the venue to talk about R as well.
> Therefore, even if it is not exactly a typical mailing list question,
> I would like to have suggestions about where to collect info about:
> (1)Institutions (not only academia) using R
> (2)Hardware requirements, possibly benchmarks
> (3)R & clusters, R & multiple CPU machines, R performance on
> different hardware.
> (4)finally, a list of the advantages for using R over commercial
> statistical packages. The money-saving in itself is not a reason good
> enough and some people are scared by the lack of professional support,
> though this mailing list is simply wonderful.
>
> Kind Regards
>
> Lorenzo Isella
>
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