The predictors and outcomes in lm can be matrices, so you could use something
like the following:
x.mat=cbind(x1=rnorm(20),x2=rnorm(20))
y.mat=cbind(y1=rnorm(20),y2=rnorm(20))
lm(y.mat~x.mat)
David Freedman
ivowel wrote:
>
> dear r-experts: there is probably a very easy way to do it, but it eludes
> me right now. I have a large data frame with, say, 26 columns named "a"
> through "z". I would like to define "sets of regressors" from this data
> frame. something like
>
> myregressors=c("b", "j", "x")
> lm( l ~ myregressors, data=... )
>
> is the best way to create new data frames that contain all the variables I
> want, then use ".", and then destroy them again? or am I overlooking
> something obvious?
>
> sincerely,
>
> /iaw
>
> [[alternative HTML version deleted]]
>
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