[R] Suggestions for statistical computing course

[Liaw, Andy]

I really like John Monahan's Numerical Methods of Statistics (Cambridge
University Press).  

As to running/editing R scripts, you may want to look into JGR.  The
built-in editor is not as "smart" as ESS in some respect, but "smarter"
than ESS in others.  The only thing that keep me from using it regularly
is the fact that it won't take arguments to R itself (at least on
Windows):  I need the --internet2 argument to be able to access the net
from R.

Andy

From: Giovanni Petris
> 
> Dear R-helpers,
> 
> I am planning a course on Statistical Computing and Computational
> Statistics for the Fall semester, aimed at first year Masters students
> in Statistics. Among the topics that I would like to cover are linear
> algebra related to least squares calculations, optimization and
> root-finding, numerical integration, Monte Carlo methods (possibly
> including MCMC), bootstrap, smoothing and nonparametric density
> estimation. Needless to say, the software I will be using is R.
> 
> 1. Does anybody have a suggestion about a book to follow that covers
>    (most of) the topics above at a reasonable revel for my audience? 
>    Are there any on-line publicly-available manuals, lecture notes,
>    instructional documents that may be useful?
> 
> 2. I do most of my work in R using Emacs and ESS. That means that I
>    keep a file in an emacs window and I submit it to R one line at a
>    time or one region at a time, making corrections and iterating as
>    needed. When I am done, I just save the file with the last,
>    working, correct (hopefully!) version of my code. Is there a way of
>    doing something like that, or in the same spirit, without using
>    Emacs/ESS? What approach would you use to polish and save your code
>    in this case? For my course I will be working in a Windows
>    environment. 
>    
>    While I am looking for simple and effective solutions that do not
>    require installing emacs in our computer lab, the answer "you
>    should teach your students emacs/ess on top of R" is perfecly
>    acceptable.
>    
> 
> Thank you for your consideration, and thank you in advance for the
> useful replies.
> 
> Have a good day,
> Giovanni
> 
> -- 
> 
> Giovanni Petris  <GPetris at uark.edu>
> Department of Mathematical Sciences
> University of Arkansas - Fayetteville, AR 72701
> Ph: (479) 575-6324, 575-8630 (fax)
> http://definetti.uark.edu/~gpetris/
> 
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> 
> 


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