Dear Kevin,
I would convert the script into a function and add it to the R folder. This
makes it easy to document the script using the standard R help files. Then
add the function to the examples in the helpfile of the data in a
\dontrun{}. Then it is clear to to user how the data was generated.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey
2016-03-23 11:46 GMT+01:00 Enrico Schumann <e...@enricoschumann.net>:
> On Tue, 22 Mar 2016, Kevin Coombes <kevin.r.coom...@gmail.com> writes:
>
> > Hi,
> >
> > I'm currently developing an R package that includes a small data set
> > along with the functions that I want to export. I have an R script
> > that generates the data set; the computation time is long (well,
> > relative to the size of the data set). So, my plan is to run the
> > script and save() the data set as an *.rda file that I can put in the
> > data directory. (It is possible that some users of the package will
> > _only_ be interested in the data set.)
> >
> > But, I'd like to keep the script with the package, both because it
> > shows how to use some of the functions and because I might want to
> > modify how the data set is generated in the future. My question: What
> > is the "best practice" for where in the package directory structure to
> > store such a script?
> >
> > Best,
> > Kevin
>
> If the script is short, you could wrap it in \dontrun{...}
> and put it into the Examples section of the Rd file that
> describes the data. In this way people can quickly find the
> code when they look up the data's documentation.
>
>
> Kind regards
> Enrico
>
>
> --
> Enrico Schumann
> Lucerne, Switzerland
> http://enricoschumann.net
>
> ______________________________________________
> R-package-devel@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-package-devel
>
[[alternative HTML version deleted]]
______________________________________________
R-package-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-package-devel
