[R] define subset argument for function lm as variable?

[Milan Bouchet-Valat]

Le mardi 21 août 2012 à 07:51 -0700, Joshua Wiley a écrit :
> Hi Rainer,
> 
> You could try:
> 
> subs <- expression(dead==FALSE & recTreat==FALSE)
> 
> lme(formula, subset = eval(subs))
> 
> Not tested, but something along those lines should work.
Out of curiosity, why isn't "subset" (and "weights", which is very
similar in that regard) evaluated in the "data" environment, just like
the formula? Is this for historical reasons, or are there drawbacks to
such a feature?

It seems very common to pass a data frame via the "data" argument, and
use variables from it for subsetting and/or weighting.


Regards


> Josh
> 
> On Tue, Aug 21, 2012 at 7:44 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:
> > Hi
> >
> > I want to do a series of linear models, and would like to define the input
> > arguments for lm() as variables. I managed easily to define the formula
> > arguments in a variable, but I also would like to have the "subset" in a
> > variable. My reasoning is, that I have the subset in the results object.
> >
> > So I wiould like to add a line like:
> >
> > subs <- dead==FALSE & recTreat==FALSE
> >
> > which obviously does not work as the expression is evaluated immediately. Is
> > is it possible to do what I want to do here, or do I have to go back to use
> >
> > dat <- subset(dat, dead==FALSE & recTreat==FALSE)
> >
> > ?
> >
> >
> >
> > dat <- loadSPECIES(SPECIES)
> > feff <- height~pHarv*year               # fixed effect in the model
> > reff <- ~year|plant                     # random effect in the model, where
> > year is the
> > dat.lme <- lme(
> >              fixed = feff,                           # fixed effect in the
> > model
> >              data  = dat,
> >              random = reff,                          # random effect in the
> > model
> >              correlation = corAR1(form=~year|plant), #
> >              subset = dead==FALSE & recTreat==FALSE, #
> >              na.action = na.omit
> >              )
> > dat.lm <- lm(
> >             formula =  feff,              # fixed effect in the model
> >             data = dat,
> >             subset = dead==FALSE & recTreat==FALSE,
> >             na.action = na.omit
> >             )
> >
> > Thanks,
> >
> > Rainer
> >
> > --
> > Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
> > UCT), Dipl. Phys. (Germany)
> >
> > Centre of Excellence for Invasion Biology
> > Stellenbosch University
> > South Africa
> >
> > Tel :       +33 - (0)9 53 10 27 44
> > Cell:       +33 - (0)6 85 62 59 98
> > Fax :       +33 - (0)9 58 10 27 44
> >
> > Fax (D):    +49 - (0)3 21 21 25 22 44
> >
> > email:      Rainer at krugs.de
> >
> > Skype:      RMkrug
> >
> > ______________________________________________
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> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> 
> 
>