To be more accurate and helpful, try this:
fun<- function(x,y){
for(i in 1:length(colnames(x))){
for(j in 1:length(colnames(y))){
if(colnames(x)[i]==colnames(y)[j]){
models=list(lm(ts(x[i])~ts(y[j])))
return(models)
}
else{}
}
}
}
:) Does this do it for you?
Daniel
hazzard wrote:
>
> Hi,
>
> I have two datasets, x and y. Simplified x and y denote:
>
> X
>
> Y
>
> A B C A B C . . . . . . . . . . . . . . . . . .
> I want to implement all possible models such as lm(X$A~Y$A), lm(X$B~Y$B),
> lm(X$C~Y$C)... I have tried the following:
>
> fun<- function(x,y){
> for(i in 1:length(colnames(x))){
> for(j in 1:length(colnames(y))){
> if(colnames(x)[i]==colnames(y)[j]){
> models=list(lm(ts(x[i])~ts(y[j])))
> }
> else{}
> }
> }
> return(models)
> }
>
> The problem is that this returns only one of the three models, namely the
> last one. What am I doing wrong? Thank you very much in advance.
>
> Regards
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> 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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