There are several ways to do this. The following is only one of the ways.
One of the advantages of this approach is that it allows including both
continuous and categorical variables.
I'll demonstrate with the iris dataset. Place your variables in a dataframe
with the y variable in the first column. Then,
out<-list()
vars<-names(iris)
out[[1]]<-lm(Sepal.Length~1,data=iris)
for(k in 2:length(vars)){
out[[k]]<-update(out[[k-1]],as.formula(paste(".~.+",vars[k],sep="")))
}
On Sun, Oct 3, 2010 at 4:29 PM, lord12 <trexi...@yahoo.com> wrote:
>
> If I have a model line = lm(y~x1) and I want to use a for loop to change
> the
> number of explanatory variables, how would I do this?
>
> So for example I want to store the model objects in a list.
>
> model1 = lm(y~x1)
> model2 = lm(y~x1+x2)
> model3 = lm(y~x1+x2+x3)
> model4 = lm(y~x1+x2+x3+x4)
> model5 = lm(y~x1+x2+x3+x4+x5)...
> model10.
>
> model_function = function(x){
> for(i in 1:x) {
> }
> If x =1, then the list will only add model1. If x =2, then the list will
> add
> both model1 and model2. If x=3, then the list will add model1 model 2 and
> model3 and so on. How do I translate this into code?
> --
> View this message in context:
> http://r.789695.n4.nabble.com/How-to-iterate-through-different-arguments-tp2953511p2953511.html
> Sent from the R help mailing list archive at Nabble.com.
>
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