R help - Apr 2009 - what is R best for; what should one learn in addition to R

Hi,

I've been working with R for a couple of years, and I've
been able to get most of the things done that I needed (sometimes in
a roundabout way). A few experienced statisticians told me that
R is best for interactive data analysis, but for large-scale
computations, one needs something else.

I understand that this all depends on what you are trying to
accomplish, and R offers many ways to make large-scale
computing possible.

I am seeking advice from those of you who do statistical
programming outside of R. What do you use, and what kinds
of applications require you to use something other than R?

I have some experience with Java, C++, and Perl. Where would you
suggest that I concentrate my efforts so that if R does not handle
what I need well, I will be equipped to handle it.

Thanks,

Juliet

On Mon, 20 Apr 2009 11:49:29 -0400 Juliet Hannah
<juliet.hannah at gmail.com> wrote:

JH> I've been working with R for a couple of years, and I've
JH> been able to get most of the things done that I needed (sometimes in
JH> a roundabout way). A few experienced statisticians told me that
JH> R is best for interactive data analysis, but for large-scale
JH> computations, one needs something else.

Depends on what is meant by large-scale computations and you yourself
intend to do. I know of people doing optimization stuff which needs a
lot of computational power. They use Matlab since it is easy for them
to use multiple processors (+multiple pc's). R at the moment only uses
one processor and also does not yet (there is a project working on it)
something like just in time compilation which appears to be in Matlab. 

However R is for free and flexible so there are ways to deal with some
analysis that need more computational power. 

my 2c
Stefan

You might also try looking in to Python. It has lots of mathematical and
computational libraries (numpy and scipy are particularly useful), as well
some to deal with concurrency (e.g. Parallel Python), and can interact with
R (rpy and rpy2).
Josh Stumpf



On Mon, Apr 20, 2009 at 8:49 AM, Juliet Hannah
<juliet.hannah@gmail.com>wrote:
> Hi,
>
> I've been working with R for a couple of years, and I've
> been able to get most of the things done that I needed (sometimes in
> a roundabout way). A few experienced statisticians told me that
> R is best for interactive data analysis, but for large-scale
> computations, one needs something else.
>
> I understand that this all depends on what you are trying to
> accomplish, and R offers many ways to make large-scale
> computing possible.
>
> I am seeking advice from those of you who do statistical
> programming outside of R. What do you use, and what kinds
> of applications require you to use something other than R?
>
> I have some experience with Java, C++, and Perl. Where would you
> suggest that I concentrate my efforts so that if R does not handle
> what I need well, I will be equipped to handle it.
>
> Thanks,
>
> Juliet
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
"Despair leads to boredom, electronic games, computer hacking, poetry, and
other bad habits." --Ed Abbey

"Masochism is a valuable job skill. ." --Chuck Palahniuk

"It is by caffeine alone I set my mind in motion. It is by the beans of
Java
that my thoughts acquire speed. My hands acquire shaking, the shaking
becomes a warning. It is by caffeine alone I set my mind in motion..."

	[[alternative HTML version deleted]]

What things you should learn in addition to R depends on what types of things
you want to do.  But here are some of the programs that I recommend people take
a look at:

gnuplot
ggobi
Imagemagick
LaTeX
xfig
Make
Emacs (or other programming editor)
SQL
Perl (or other scripting language)
Tk (actually more an extension than a language/package)

I also recommend that people doing statistics know at least the basics of 3
different stats packages (S-Plus and R don't count as 2 separate packages)

Depending on your situation, some of the above may be useful, others may not. 
And things can change, I find myself using Perl much less than I used to (but am
still glad to have it as one of my tools).

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Juliet Hannah
> Sent: Monday, April 20, 2009 9:49 AM
> To: r-help at r-project.org
> Subject: [R] what is R best for; what should one learn in addition to R
> 
> Hi,
> 
> I've been working with R for a couple of years, and I've
> been able to get most of the things done that I needed (sometimes in
> a roundabout way). A few experienced statisticians told me that
> R is best for interactive data analysis, but for large-scale
> computations, one needs something else.
> 
> I understand that this all depends on what you are trying to
> accomplish, and R offers many ways to make large-scale
> computing possible.
> 
> I am seeking advice from those of you who do statistical
> programming outside of R. What do you use, and what kinds
> of applications require you to use something other than R?
> 
> I have some experience with Java, C++, and Perl. Where would you
> suggest that I concentrate my efforts so that if R does not handle
> what I need well, I will be equipped to handle it.
> 
> Thanks,
> 
> Juliet
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.