[R] Pros and Cons of R

[Bert Gunter]

 This is about the 8761st time that this old warhorse has been discussed on
this list. I suggest you search the archives (e.g. via CRAN, Gmane,
Google,...) for these prior discussions.

-- Bert Gunter
Genentech

P.S. Incidentally, the answer to your question is "It depends..." -- on what
your applications/needs are, on what your statistical computing resources
are, and most importantly, on what your users are willing to put into using
it.



Hi,

I am doing a very informal presentation for my office about R capabilities
to deal with and analyze spatial data, display data and maps, and
connections with GIS. I've used in my presentation info from the CRAN, the
spatial Task view, and the more striking graphics examples from
http://addictedtor.free.fr/graphiques/thumbs.php and NCEAS
http://www.nceas.ucsb.edu/scicomp/GISSeminar/UseCases/MapProdWithRGraphics/O
neMapProdWithRGraphics.html together with examples of my own work.

I am finishing with pros and cons about R and I am wondering if you can come
up with other examples, or comments. Here they are:

Pros:

- R is a programming environment well suited for statistical analysis.
- R is open source and cross platforms (Windows, Mac, Linux).
- Fortran, C (C++), and Python wrappers are in place.
- Deals well with spatial data, has a robust graphical interface and has an
active user group list / forum.
- External packages for R are almost daily increasing, most of them based on
published up-to-date books and peer-reviewed articles.
- R related books - quite a few ..

Cons:

- R has a very steep learning curve.
- There is no perfect "beginner" book.
- Experience with other programming languages is a plus / minus.
- You can save scripts, but not *.exe.
- It is updated several times a year (good) but there are no up-grades.
- It seems that it is hard to install correctly under Linux.
- Everything you want to do is a command line, minimal GUI.
- Memory management problems (depends on your OS), especially when
displaying big images at high resolution or working with huge matrices
(hundreds of Mb).

Also i am wondering if R works under 64 bit computers and if it takes
advantage of it.

Thanks,

Monica

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