Re: [R] function in nls argument -- robust estimation

Hi Kate and others, thanks for the info. Btw, you sent the different methods to analyze the data: nls, nls.lm and nlrob. Comparing the results visually nlrob performed better then nls, but nls.lm (using the 0.9 quantile of residuals) was still better than nlrob. My data may have a rather large

Re: [R] function in nls argument -- robust estimation

Hi Kate and Fernando, I'm late into this thread, but from reading it I get the impression that Fernando really wants to do *robust* (as opposed to least-squares) non-linear model fitting. His proposal to set residuals to zero when they are outside a given bound is a very special case of an

Re: [R] function in nls argument -- robust estimation

Dear Martin, Thanks for the ideas regarding the relation of what Fernando is doing with robust regression. Indeed, it's an important point that he can't consider the standard error estimates on his parameters correct. I know from discussion off-list that he's happy with the results he has now;