In package relaimpo in R, we measure the relative importance with different methods. However, the $R^2$ for all the methods is similar.
Is it supposed to be similar or a bug?
In package relaimpo in R, we measure the relative importance with different methods. However, the $R^2$ for all the methods is similar.
Is it supposed to be similar or a bug?
$R^2$ measures fit of the model, not of particular variables.
From the documentation (bold added by myself):
Five of the metrics in
calc.relimp(lmg,pmvd,pratt,geniziandcar), decompose the model $R^2$.calc.relimp(lmg,pmvd,pratt,geniziandcar) sum to the $R^2$ that is to be decomposed [...]
You can find out more about the methods from the references provided in the documentation.
Notice however that $R^2$ can be misleading and does not really tell you about "variance explained" unless you are using linear regression.