[Rd] Projects

[Peter Dalgaard BSA]

Douglas Bates <bates@stat.wisc.edu> writes:

> I am teaching a graduate course on Statistical Computing this
> semester.  A major part of the grade is determined by a project in
> which a student or small group of students produce, test, and document
> some software for statistics.  I will encourage those students who are
> developing in S to package their software as an R package.
> 
> I would welcome suggestions of possible projects, especially projects
> that come under the heading of "Useful facilities to be added to R".
> Please keep in mind that the project must be completed by mid-December
> and that not all the students have extensive experience programming in
> S and C.

These are probably too hard and too narrow, but now the topic is up:

- getting predictions to work on new data in cases where model depends
  on data set (notably regressions splines with auto knot placement)

- in lme, we can predict at level K would be nice to get SE of
  prediction (this also takes levels, extending distinction between
  confidence and tolerance intervals) 

- conditional tolerance in lme (much too hard I suspect)

- in model.tables.aov, SE's for type="means" are sorely missed.

This is not very hard, but maybe too small (although one will have to
study issues of contrasts and internals of an lm object rather
carefully):

- extend pairwise.t.test to take a linear model and a factor in the
  model as argument. 

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk)             FAX: (+45) 35327907
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