[R]...Why social scientists don't use R
Prof Brian Ripley
ripley at stats.ox.ac.uk
Wed Aug 18 21:40:12 CEST 2004
On Wed, 18 Aug 2004, Cliff Lunneborg wrote:
> Berton Gunter has written in part:
> > A few comments:
> > First, your remarks are interesting and, I would say, mainly well
> founded. However, I think they > are in many respects irrelevant,
> although they do point to the much bigger underlying issue,
> > which Roger Peng also hinted at in his reply.
> > I think they are sensible because R IS difficult; the documentation is
> often challenging, which is
> > not surprising given (a) the inherent complexity of R; (b) the
> difficulty in writing good
> > documentation, especially when many of the functions being documented
> are inherently
> > technical, so subject matter knowledge (CS, statistics, numerical
> analysis ,...) must be
> > assumed;
> My experience has been that the real challenge is not understanding the
> documentation, but finding it. Once I know the names of one or more
> candidate functions I am happily on my way. One of the delights of
> reading r-help is that one keeps discovering useful functions. In the
> best of all possible worlds I could ask an intelligent agent to summon
> up the k-nearest neighbor functions that would "do X." Not likely.
help.search does a better job than it is given credit for.
> Years ago StatSci Europe published a handy little "Complete Listing of
> S-PLUS Functions", categorized in some way. I found it useful. Something
> similar for R would not go amiss. I know, it would want to be 420 pages
> rather than 42.
What is R in this context? There are several hundred addons on CRAN, BioC
and elsewhere. R's HTML search or help.search will give you a complete
listing over installed packages by `keyword', which is what the `Complete
Listing of S-PLUS Functions' I saw was about.
Windows users should try the full-text searches in CHM help, especially
for package stats.
The problem is to know what to search for. To pick a recent example,
to use `logistic-normal model' for a random-intercept GLMM is not going to
work, but Googling will usually bring up synonyms.
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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