I am using the package "relaimpo" to calculate the relative importance of variables that I have fitted to a linear model. Code is:
It is returning me outputs like these:
> calc.relimp(model,rela=TRUE) Response variable: Sales Total response variance: 3505.987 Analysis based on 20 observations 2 Regressors: Price Advertising Proportion of variance explained by model: 53.51% Metrics are normalized to sum to 100% (rela=TRUE). Relative importance metrics: lmg Price 0.2246168 Advertising 0.7753832 Average coefficients for different model sizes: 1X 2Xs Price -16.92037 -21.71100 Advertising 68.88305 74.38533
I understand that ultimately I just need to look at the relative importance metrics for both variables (ie 22.5% for Price and 77.5% for Advertising). But what do the numbers in "Average coefficients for different model sizes" mean? Thanks.