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, [EMAIL PROTECTED] 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 ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
