Let's say I have a data matrix d
pc = prcomp(d)
# pc1 and pc2 are the principal components
pc1 = pc$rotation[,1]
pc2 = pc$rotation[,2]
Then this should fit the linear regression model right?
r = lm(y ~ pc1+pc2)
But then I get this error :
Errormodel.frame.default(formula = y ~ pc1+pc2, drop.unused.levels = TRUE) :
unequal dimensions('pc1')
I guess there a packages out there who do this automatically, but this should work too?