[Rd] Documentation examples for lm and glm

[Martin Maechler]

>>>>> David Hugh-Jones 
>>>>>     on Sat, 15 Dec 2018 08:47:28 +0100 writes:

    > I would argue examples should encourage good
    > practice. Beginners ought to learn to keep data in data
    > frames and not to overuse attach(). 

Note there's no attach() there in any of these examples!

    > otherwise at their own risk, but they have less need of
    > explicit examples.

The glm examples are nice in sofar they show both uses.

I agree the lm() example(s) are  "didactically misleading" by
not using data frames at all.

I disagree that only data frame examples should be shown.
If  lm()  is one of the first R functions a beginneR must use --
because they are in a basic stats class, say --  it may be
*better* didactically to focus on lm()  in the very first
example, and use data frames in a next one ...
.... and instead of next one, we have the pretty clear comment
     
  ### less simple examples in "See Also" above

I'm not convinced (but you can try more) we should change those
examples or add more there.

Martin

    > On Fri, 14 Dec 2018 at 14:51, S Ellison
    > <S.Ellison using lgcgroup.com> wrote:

    >> FWIW, before all the examples are changed to data frame
    >> variants, I think there's fairly good reason to have at
    >> least _one_ example that does _not_ place variables in a
    >> data frame.
    >> 
    >> The data argument in lm() is optional. And there is more
    >> than one way to manage data in a project. I personally
    >> don't much like lots of stray variables lurking about,
    >> but if those are the only variables out there and we can
    >> be sure they aren't affected by other code, it's hardly
    >> essential to create a data frame to hold something you
    >> already have.  Also, attach() is still part of R, for
    >> those folk who have a data frame but want to reference
    >> the contents across a wider range of functions without
    >> using with() a lot. lm() can reasonably omit the data
    >> argument there, too.
    >> 
    >> So while there are good reasons to use data frames, there
    >> are also good reasons to provide examples that don't.
    >> 
    >> Steve Ellison
    >> 
    >> 
    >> > -----Original Message----- > From: R-devel
    >> [mailto:r-devel-bounces using r-project.org] On Behalf Of Ben >
    >> Bolker > Sent: 13 December 2018 20:36 > To:
    >> r-devel using r-project.org > Subject: Re: [Rd] Documentation
    >> examples for lm and glm
    >> >
    >> >
    >> > Agree.  Or just create the data frame with those
    >> variables in it > directly ...
    >> >
    >> > On 2018-12-13 3:26 p.m., Thomas Yee wrote: > > Hello,
    >> > >
    >> > > something that has been on my mind for a decade or
    >> two has > > been the examples for lm() and glm(). They
    >> encourage poor style > > because of mismanagement of data
    >> frames. Also, having the > > variables in a data frame
    >> means that predict() > > is more likely to work properly.
    >> > >
    >> > > For lm(), the variables should be put into a data
    >> frame.  > > As 2 vectors are assigned first in the
    >> general workspace they > > should be deleted afterwards.
    >> > >
    >> > > For the glm(), the data frame d.AD is constructed but
    >> not used. Also, > > its 3 components were assigned first
    >> in the general workspace, so they > > float around
    >> dangerously afterwards like in the lm() example.
    >> > >
    >> > > Rather than attached improved .Rd files here, they
    >> are put at > > www.stat.auckland.ac.nz/~yee/Rdfiles > >
    >> You are welcome to use them!
    >> > >
    >> > > Best,
    >> > >
    >> > > Thomas
    >> > >
    >> > > ______________________________________________ > >
    >> R-devel using r-project.org mailing list > >
    >> https://stat.ethz.ch/mailman/listinfo/r-devel
    >> >
    >> > ______________________________________________ >
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