I am using the package "relaimpo" to calculate the relative importance of variables that I have fitted to a linear model. Code is:

```
calc.relimp(model,rela=TRUE)
```

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.