I've been using the `lm` function in R to do demand modeling (tons of steel to be predicted by various economic indicators). I used $R^2$ and $F$ to report on the strength of the model. However, when I use the R function `lqs` ("resistant regression") and then type in `summary(model_name)` I do not get any statistics that I can use to report on the strength of the regression model. Any suggestions?

EDIT:
Thanks for your quick response. I don't have a problem with lqs(). The problem is that when I type in summary(Model) I do not get any goodness of fit information (e.g., adjusted R squared) as I do when I enter summary(x) where X is a model created using the lm function. I'd like to have something to show the strength of the model. I"m using MASS. See below.

```
library(MASS)

M10 = lqs(agri ~ p12 + p1 + p11 + p5 + p8 + p6 + p25 + p50 + p35,
          data = agri_data2) 
summary(M10) 
Length Class Mode
crit 1 -none- numeric
sing 1 -none- character coefficients 10 -none- numeric
bestone 10 -none- numeric
fitted.values 103 -none- numeric
residuals 103 -none- numeric
scale 2 -none- numeric
terms 3 terms call
call 3 -none- call
xlevels 0 -none- list
model 10 data.frame list 

```