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...non-linear regression as in Ch8.10 of MASS. I understand that nnet() by default optimizes least squares. I'm looking to have it instead optimize such that the mean error is zero (so that it is unbiased). Any suggestions on how this might be achieved? Cheers, Mike -- Mike Lawrence http://artsweb.uwaterloo.ca/~m4lawren "The road to wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less." - Piet Hein

...it transformed y values): my.lm.obj=lm(qlogis(y)~x,weights=w) I get an error because, of course, logit(1) = log(1/0) = log(Inf) = Inf (similarly, logit(0) = log(0/1) = log(0) = -Inf). I'd be very interested to see how glm deals with these extremes. Cheers, Mike -- Mike Lawrence http://artsweb.uwaterloo.ca/~m4lawren "The road to wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less." - Piet Hein

...k[i])/n) } ecdf.area=sum(ecdf.area) #again, subtraction of the areas works if the ecdf is consistently lower #than the cdf diff=cdf.area-ecdf.area #or consistently higher than the cdf diff=ecdf.area-cdf.area #but how to calculate when the functions cross? Cheers, Mike -- Mike Lawrence http://artsweb.uwaterloo.ca/~m4lawren "The road to wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less." - Piet Hein