[R] things that are difficult/impossible to do in SAS or SPSSbut simple in R

[hadley wickham]

On Jan 18, 2008 1:19 PM, Jeffrey J. Hallman <jhallman at frb.gov> wrote:
> Frank E Harrell Jr <f.harrell at vanderbilt.edu> writes:
>
> > Rob Robinson wrote:
> >> I wonder if those who complain about SAS as a programming environment have
> >> discovered SAS/IML which provides a programming environment akin to Matlab
> >> which is more than capable (at least for those problems which can be treated
> >> with a matrix like approach). As someone who uses both SAS and R - graphical
> >> output is so much easier in R, but for handling large 'messy' datasets SAS
> >> wins hands down...
> >> Cheers
> >> Rob
> >
> > My understanding is that PROC IML is disconnected from the rest of the
> > SAS language, e.g., you can't have a loop in which PROC GENMOD is called
> > or datasets are merged.  If that's the case, IML is not very competitive
> > in my view.
>
> I know about IML, but have never really used it.  Back when I was doing that
> kind of stuff (before discovering S-Plus) I used GAUSS for compute-intensive
> matrix simulations and the like.  I didn't have SAS for my PC, and there was
> no way I could tie up the Sun boxes at work with simulations for my thesis.
>
> But while IML does some nice stuff, it just reinforces the point I made in
> another post about the proliferation of "little languages" in SAS.  By my count,
> that are now 5:
>
> 1.  data step programming
> 2.  macros -- a 'language' grafted on top of data step programming
> 3.  scl -- if you want to do any kind of user interface
> 4.  af  -- object-oriented framework built on top of scl
> 5.  iml -- matrix language like GAUSS, but doesn't play well with 1:4 above.

6. the "proc" language

Hadley

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