R-beta: S compatibility
maechler at stat.math.ethz.ch
Fri Aug 14 14:21:29 CEST 1998
>>>>> "Jim" == Jim Lindsey <jlindsey at alpha.luc.ac.be> writes:
Jim> Once again, I foolishly attempted a major port of S, ratfor, and
Jim> Fortran code (hidden Markov models from an article in the latest Can
Jim> Jr Stat) to R without access to S-Plus itself. Here are some problems
Jim> I found before abandoning:
Jim> 1. replicating a factor does not give a factor:
Jim> is.factor(rep(gl(2,1,2),2)) is FALSE
This *is* S-plus compatible!
[Try rep(factor(1:3), 2) ]
(even though I agree that I'd like to see a factor myself in that case.
... again: Should we be compatible or fix inconsistencies .. ? (;-))
Jim> 2. sample() does not have the option, prob=
yes. Volunteers to add it ?
Jim> 3. glm()$assign does not exist
yes. Volunteers to add it ? [the same for lm()$assign]
Jim> 4. glm()$contrast is very different from S - apparently the latter is
Jim> a list with one member per variable instead of a copy of the options
Jim> in effect
The next (0.63) version of R will have the same as S, here (I think).
WARNING: The current snapshot of 0.63 is currently somewhat ``more unstable''
Jim> 5. C() does not exist (something to do with contrasts, which are
Jim> apparently handled much differently in S-Plus)
Jim> 6. dummy.coef() does not exist
Brian Ripley's aov package which should also make it's way into R 0.63,
has model.tables() which provides even more than dummy.coef..
Any volunteers (maybe after 0.63) for doing
C() [maybe not so easy]
dummy.coef [should be easy/trivial, if you have model.tables]
Jim> 7. something else I have now forgotten...
Jim> In general, almost all aspects of model fitting in the two seem to be
Jim> completely incompatible.
This is true if you look at the ``low-level'' structure of returned
However, the ``normal user interface'' is VERY compatible
Also, many of the accessor functions
[coef(), resid(), effects(), summary(), predict()]
return the same thing or something very close to S's.
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