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

[Thomas Frööjd]

As far as i know mixture modelling (sums of exponentials) cant be done
in SAS or SPSS. For R there is the Rmix package that while not very
user friendly at least works.

On Jan 15, 2008 8:45 PM, Matthew Keller <mckellercran at gmail.com> wrote:
> Hi all,
>
> I'm giving a talk in a few days to a group of psychology faculty and
> grad students re the R statistical language. Most people in my dept.
> use SAS or SPSS. It occurred to me that it would be nice to have a few
> concrete examples of things that are fairly straightforward to do in R
> but that are difficult or impossible to do in SAS or SPSS. However, it
> has been so long since I have used either of those commercial products
> that I am drawing a blank. I've searched the forums and web for a list
> and came up with just Bob Muenchen's comparison of general procedures
> and Patrick Burns' overview of the three. Neither of these give
> concrete examples of statistical problems that are easily solved in R
> but not the commercial packages.
>
> Can anyone more familiar with SAS or SPSS think of some examples of
> problems that they couldn't do in one of those packages but that could
> be done easily in R? Similarly, if there are any examples of the
> converse I would also be interested to know.
>
> Best,
>
> Matt
>
> --
> Matthew C Keller
> Asst. Professor of Psychology
> University of Colorado at Boulder
> www.matthewckeller.com
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>