From: Gavin Simpson <gavin.simpson_at_ucl.ac.uk>

Date: Thu 18 Aug 2005 - 13:22:59 GMT

Date: Thu 18 Aug 2005 - 13:22:59 GMT

On Thu, 2005-08-18 at 09:00 -0400, Gabor Grothendieck wrote:

*> I think this one is a hard call. Designing software is a
**> series of tradeoffs. Its nice to maintain consistency with
**> the R base, but in case of extensions (rather than changing
**> behavior) as in this case, the argument against the change
**> carries less weight.
**>
**> The main problems with extensions are (1) that one has to
**> remember which functions/packages have which extensions if
**> one is to use them and (2) they can interfere with other
**> future extensions.
**>
**> On the other hand, if one is using a particular package a
**> lot then convenience features like this may be attractive.
**> Also, packages are where authors have the freedom to try out
**> new ideas and new functionality without being constrained.
**>
**> Perhaps, if the extension in question is added there could be
**> a warning in the help file that this is a convenience feature
*

> of this particular package and is not generally available

> throughout R.

Thanks again Gabor for another useful contribution to this debate. Also thanks to Martin, Gabor and Jari for their comments, ideas, suggestions and viewpoints.

I still like y1 ~ y2 (both data frames), but during my bike ride to work this morning I considered both sides of the argument and my position has moved towards the R way of doing things - far be it for little old me to go against years of S-formula tradition. So I'll revert the code back to accepting y1 ~ ., data = y2 and leave it to throw an error for the rhs being a data frame case.

Once again, thank you for helping me work through this dilemma.

All the best,

Gav

*> On 8/18/05, Gavin Simpson <gavin.simpson@ucl.ac.uk> wrote:
*

> > On Thu, 2005-08-18 at 07:57 +0300, Jari Oksanen wrote:

*> > > On 18 Aug 2005, at 1:49, Gavin Simpson wrote:
**> > >
**> > > > On Wed, 2005-08-17 at 20:24 +0200, Martin Maechler wrote:
**> > > >>>>>>> "GS" == Gavin Simpson <gavin.simpson@ucl.ac.uk>
**> > > >>>>>>> on Tue, 16 Aug 2005 18:44:23 +0100 writes:
**> > > >>
**> > > >> GS> On Tue, 2005-08-16 at 12:35 -0400, Gabor Grothendieck
**> > > >> GS> wrote:
**> > > >>>> On 8/16/05, Gavin Simpson <gavin.simpson@ucl.ac.uk>
**> > > >>>> wrote: > On Tue, 2005-08-16 at 11:25 -0400, Gabor
**> > > >>>> Grothendieck wrote: > > It can handle data frames like
**> > > >>>> this:
**> > > >>>>>>
**> > > >>>>>> model.frame(y1) > > or > > model.frame(~., y1)
**> > > >>>>>
**> > > >>>>> Thanks Gabor,
**> > > >>>>>
**> > > >>>>> Yes, I know that works, but I want the function
**> > > >>>> coca.formula to accept a > formula like this y2 ~ y1,
**> > > >>>> with both y1 and y2 being data frames. It is
**> > > >>>>
**> > > >>>> The expressions I gave work generally (i.e. lm, glm,
**> > > >>>> ...), not just in model.matrix, so would it be ok if the
**> > > >>>> user just does this?
**> > > >>>>
**> > > >>>> yourfunction(y2 ~., y1)
**> > > >>
**> > > >> GS> Thanks again Gabor for your comments,
**> > > >>
**> > > >> GS> I'd prefer the y1 ~ y2 as data frames - as this is the
**> > > >> GS> most natural way of doing things. I'd like to have (y2
**> > > >> GS> ~., y1) as well, and (y2 ~ spp1 + spp2 + spp3, y1) also
**> > > >> GS> work - silently without any trouble.
**> > > >>
**> > > >> I'm sorry, Gavin, I tend to disagree quite a bit.
**> > > >>
**> > > >> The formula notation has quite a history in the S language, and
**> > > >> AFAIK never was the idea to use data.frames as formula
**> > > >> components, but rather as "environments" in which formula
**> > > >> components are looked up --- exactly as Gabor has explained.
**> > > >
**> > > > Hi Martin, thanks for your comments,
**> > > >
**> > > > But then one could have a matrix of variables on the rhs of the formula
**> > > > and it would work - whether this is a documented feature or un-intended
**> > > > side-effect of matrices being stored as vectors with dims, I don't
**> > > > know.
**> > > >
**> > > > And whilst the formula may have a long history, a number of packages
**> > > > have extended the interface to implement a specific feature, which
**> > > > don't
**> > > > work with standard functions like lm, glm and friends. I don't see how
**> > > > what I wanted to achieve is greatly different to that or using a
**> > > > matrix.
**> > > >
**> > > >> To break with such a deeply rooted principle,
**> > > >> you should have very very good reasons, because you're breaking
**> > > >> the concepts on which all other uses of formulae are based.
**> > > >> And this would potentially lead to much confusion of your users,
**> > > >> at least in the way they should learn to think about what
**> > > >> formulae mean.
**> > > >
**> > > > In the end I managed to treat y1 ~ y2 (both data frames) as a special
**> > > > case, which allows the existing formula notation to work as well, so I
**> > > > can use y1 ~ y2, y1 ~ ., data = y2, or y1 ~ var + var2, data = y2. This
**> > > > is what I wanted all along, to extend my interface (not do anything to
**> > > > R's formulae), but to also work in the traditional sense.
**> > > >
**> > > > The model I am writing code for really is modelling the relationship
**> > > > between two matrices of data. In one version of the method, there is
**> > > > real equivalence between both sides of the formula so it would seem odd
**> > > > to treat the two sides of the formula differently. At least to me ;-)
**> > >
**> > > It seems that I may be responsible for one of these extensions (lhs as
**> > > a data.frame in cca and rda in vegan package). There the response (lhs)
**> > > is multivariate or a multispecies community, and you must take that as
**> > > a whole without manipulation (and if you tried using VGAM you see there
**> > > really is painful to define lhs with, say, 127 elements).
**> >
**> > Hi Jari,
**> >
**> > Thanks for reminding me about this - I'd forgotten about not normally
**> > being able to have a data.frame on the lhs of the formula either - I'm
**> > surprised no-one pulled me up on that one before, either ;-)
**> >
**> > I guess what I'm proposing is really pushing the formula representation
**> > too far for some people. I'm coming round to the y1 ~ ., data = y2 way
**> > of doing things - still prefer y1 ~ y2 though ;-)
**> >
**> > Also, both y1 and y2 are community matrices (i.e. both have many, many
**> > species, aka variables for the non-community ecologists reading this).
**> > I'm not sure that it makes sense to treat the two sides differently. In
**> > the predictive co-correspondence mode (the default), multivariate pls is
**> > used to regress one matrix on another, with the number of pls components
**> > being chosen by cross-validation or a permutation test.
**> >
**> > > However, in
**> > > general you shouldn't use models where you use all the 'explanatory'
**> > > variables (rhs) that yo happen to have by accident. So much bad science
**> > > has been created with that approach even in your field, Gav.
**> >
**> > Well, I agree with you there...
**> >
**> > > The whole
**> > > idea of formula is the ability to choose from candidate variables. That
**> > > is: to build a model. Therefore you have one-sided formulae in prcomp()
**> > > and princomp(): you can say prcomp(~ x1 + log(x2) +x4, data) or
**> > > prcomp(~ . - x3, data). I think you should try to keep it so. Do
**> > > instead like Gabor suggested: you could have a function coca.default or
**> > > coca.matrix with interface:
**> > >
**> > > coca.matrix(matx, maty, matz) -- or you can name this as coca.default.
**> > >
**> > > and coca.formula which essentially parses your formula and returns a
**> > > list of matrices you need:
**> > >
**> > > coca.formula <- function(formula, data)
**> > > {
**> > > matricesout <- parsemyformula(formula, data)
**> > > coca(matricesout$matx, matricesout$maty, matricesoutz)
**> > > }
**> > > Then you need the generic: coca <- function(...) UseMethod("coca") and
**> > > it's done (but fails in R CMD check unless you add "..." in all
**> > > specific functions...). The real work is always done in coca.matrix (or
**> > > coca.default), and the others just chew your data into suitable form
**> > > for your workhorse.
**> > >
**> > > If then somebody thinks that they need all possible variables as
**> > > 'explanatory' variables (or perhaps constraints in your case), they
**> > > just call the function as
**> > >
**> > > coca(matx, maty, matz)
**> >
**> > My functions are already generic with coca.default and coca.formula. The
**> > issue with matrices/data.frames was only a problem in the formula
**> > interface.
**> >
**> > > And if you have coca.data.frame they don't need 'quacking' with extra
**> > > steps:
**> > >
**> > > coca.data.frame <- function(dfx, dfy dfz) coca(as.matrix(dfx),
**> > > as.matrix(dfy), as.matrix(dfz)).
**> > >
**> > > This you call as coca(dfx, dfy, dfz) and there you go.
**> > >
**> > > The essential feature in formula is the ability to define the model.
**> > > Don't give it away.
**> >
**> > I think the point I'm trying to make is that I don't think what I'm
**> > trying to do is any different than doing lm(y ~ x, data), (where y, x
**> > are vectors) - it is just that my x and y happen to be multivariate. I
**> > think it is easier to think of each community as a single entity in this
**> > regard - the relationship *is* between community 1 and community 2, not
**> > parts of community 2, or some parsimonious model of community 2 - but
**> > that might just be semantics - unlike your cca/rda functions which
**> > really are a (weighted) multivariate multiple regression. Happy to be
**> > convinced otherwise though.
**> >
**> > Also, it is worth re-iterating that I haven't broken the traditional way
**> > of working with formulae with my function - you can still do y1 ~ .,
**> > data = y2, or y1 ~ spp1 + spp2 + spp3, data = y2, for maximum
**> > flexibility. All I wanted (and worked out how) to do was treat the rhs
**> > in a special way if it were a data frame, just like Jari treats a
**> > data.frame on the lhs of formulae in package vegan as a special case.
**> >
**> > Thanks everyone for your ideas and comments - lots of food for thought.
**> > I wavering between both camps on this - still time to be convinced and
**> > change it before I finish the package.
**> >
**> > All the best,
**> >
**> > G
**> >
**> > >
**> > > cheers, jazza
**> > > --
**> > > Jari Oksanen, Oulu, Finland
**> > >
**> > --
**> > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
**> > Gavin Simpson [T] +44 (0)20 7679 5522
**> > ENSIS Research Fellow [F] +44 (0)20 7679 7565
**> > ENSIS Ltd. & ECRC [E] gavin.simpsonATNOSPAMucl.ac.uk
**> > UCL Department of Geography [W] http://www.ucl.ac.uk/~ucfagls/cv/
**> > 26 Bedford Way [W] http://www.ucl.ac.uk/~ucfagls/
**> > London. WC1H 0AP.
**> > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
**> >
**> > ______________________________________________
**> > R-devel@r-project.org mailing list
**> > https://stat.ethz.ch/mailman/listinfo/r-devel
**> >
*

-- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Gavin Simpson [T] +44 (0)20 7679 5522 ENSIS Research Fellow [F] +44 (0)20 7679 7565 ENSIS Ltd. & ECRC [E] gavin.simpsonATNOSPAMucl.ac.uk UCL Department of Geography [W] http://www.ucl.ac.uk/~ucfagls/cv/ 26 Bedford Way [W] http://www.ucl.ac.uk/~ucfagls/ London. WC1H 0AP. %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-develReceived on Fri Aug 19 20:36:26 2005

*
This archive was generated by hypermail 2.1.8
: Mon 24 Oct 2005 - 22:27:40 GMT
*