search for: all_residuals

...write this as a weighted non-linear regression where the weights are recalculated during the iterations in nlme it is possible to specify weights, possibly that is the way to do it, but I didn't manage to get it working the weights should then be something like: SUM (log(1+(resid(.)/quantile(all_residuals,0.68))^2)) / SUM (resid(.)) the test data I use : x<-seq(-5,-2,length=50) x<-rep(x,4) y<-SSfpl(x,0,100,-3.5,1) y<-y+rnorm(length(y),sd=5) y[sample(1:length(y),floor(length(y)/50))]<-200 # add 2% outliers at 200 thanks a lot Hans Vermeiren [[alternative HTML version deleted]]