[R] A comment about R:

[Milos Zarkovic]

I am just beginning to use R. And I am just clinical endocrinologist, not 
statistician.

R is definitively not for casual user. Learning curve is very steep and 
previous experience in programming is essential. Therefore, some kind of 
menu system is extremely useful. I use combination of R-Commander and 
SciViews which is good, but some more functionality would be nice. On the 
other hand, function returning an object is great, as is simultaneous 
presence of multiple data sets.

Introductory documentation is excellent, both in electronic and paper form 
(books by Verzani, Dalgaard, Venables et al, Maindonald etc - not to forget 
Zoonekynd and The R Graph Gallery). However, package documentation is 
consistently cryptic (written for experts?)  - examples with explanations 
would be nice. I believe that database of packages and methods would help to 
find appropriate package.

This list is impressive. People are knowledgable, opinionated, ready to help 
and to flame you for asking elementary question or asking how to use type 
III SSQ. So, speak softly and carry a beagle. Seriously, sometimes it would 
be quicker just to give an answer, than to flame a poor soul.





Milos Zarkovic



******************************************************
Milos Zarkovic MD, Ph.D.
Associate Professor of Internal Medicine
Institute of Endocrinology
Dr Subotica 13
11000 Beograd
Serbia

Tel +381-63-202-925
Fax +381-11-685-357

Email mzarkov at eunet.yu
******************************************************



----- Original Message ----- 
From: "Kjetil Halvorsen" <kjetilbrinchmannhalvorsen at gmail.com>
To: <R-help at stat.math.ethz.ch>
Sent: Sunday, January 01, 2006 3:36 PM
Subject: [R] A comment about R:


> Readers of this list might be interested in the following commenta about 
> R.
>
>
> In a recent report, by Michael N. Mitchell
> http://www.ats.ucla.edu/stat/technicalreports/
> says about R:
>
>
> "Perhaps the most notable exception to this discussion is R, a language 
> for
> statistical computing and graphics.
> R is free to download under the terms of the GNU General Public License 
> (see
> http://www.r-project.
> org/). Our web site has resources on R and I have tried, sometimes in 
> great
> earnest, to learn and understand
> R. I have learned and used a number of statistical packages (well over 10)
> and a number of programming
> languages (over 5), and I regret to say that I have had enormous 
> diffculties
> learning and using R. I know
> that R has a great fan base composed of skilled and excellent 
> statisticians,
> and that includes many people
> from the UCLA statistics department. However, I feel like R is not so much
> of a statistical package as much
> as it is a statistical programming environment that has many new and 
> cutting
> edge features. For me learning
> R has been very diffcult and I have had a very hard time finding answers 
> to
> many questions about using
> it. Since the R community tends to be composed of experts deeply enmeshed 
> in
> R, I often felt that I was
> missing half of the pieces of the puzzle when reading information about 
> the
> use of R { it often feels like there
> is an assumption that readers are also experts in R. I often found the
> documentation for R quite sparse and
> many essential terms or constructs were used but not defined or
> cross-referenced. While there are mailing
> lists regarding R where people can ask questions, there is no offcial
> "technical support". Because R is free
> and is based on the contributions of the R community, it is extremely
> extensible and programmable and I
> have been told that it has many cutting edge features, some not available
> anywhere else. Although R is free,
> it may be more costly in terms of your time to learn, use, and obtain
> support for it.
> My feeling is that R is much more suited to the sort of statistician who 
> is
> oriented towards working
> very deeply with it. I think R is the kind of package that you really need
> to become immersed in (like a
> foreign language) and then need to use on a regular basis. I think that it
> is much more diffcult to use it
> casually as compared to SAS, Stata or SPSS. But by devoting time and 
> effort
> to it would give you access
> to a programming environment where you can write R programs and 
> collaborate
> with others who are also
> using R. Those who are able to access its power, even at an applied level,
> would be able to access tools that
> may not be found in other packages, but this might come with a serious
> investment of time to suffciently
> use R and maintain your skills with R."
>
>
> Kjetil
>
> [[alternative HTML version deleted]]
>
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