Using the builtin anscombe data set try this where we note that
the first 4 columns are x1, ..., x4 and the fifth column is y1.
for(i in 1:4) print(coef(lm(y1 ~., anscombe[c(1:i, 5)])))
On 12/6/06, Brooke LaFlamme <[EMAIL PROTECTED]> wrote:
> Hi all,
>
> I am running R version 2.4.0 on Windows XP. I am new and have the following
> question:
>
> I have a dataset of columns named x1, x2, x3...xn. I would like to write a
> linear regression using lm that looks like this:
>
> lm(y~x1+x2+x3+...+xn)
>
> If I try to use the following code, I only get the model for y~x1+xn:
>
> n<-ncol(dataset)
> model<-lm(y~x1)
> for(i in 1:n) {
> model.new<-update(model, .~.+dataset[,i])
> }
> The purpose of this is so I can use stepAIC with model.new as the upper scope
> and model as the lower.
>
> I know there must be a simple way to do this, but I am not yet familiar with
> much syntax. Any help appreciated!
> --
> Brooke LaFlamme
> Cornell University
>
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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.
>
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