Could you please advise whether studentized residuals are meaningful when computed on a robust linear regression model using an M-estimator?
I'd like to use it to detect outliers by doing something like this:
rfit = rlm(y~x, data=d) pt(rstudent(rfit), df=nrow(d)-3)
Is this reasonable? I'd be quite happy with a rather crude measure and I'd rather err on the conservative side.
I'm also wondering whether I should run some kind of diagnostic of the general goodness of fit on this robust model before doing this.