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. Regards, Bill Yarberry
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