for loop and linear models
Hi, can you put "return(models)" within the inner braces and report what it does. That might do the trick, since it should return the 'models' for every combination of i and j. HTH, 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
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