Your understanding isn't similar to mine. Mine says robust/resistant methods are for data with heavy tails, not heteroscedasticity. The common ways to approach heteroscedasticity are transformation and weighting. The first is easy and usually quite effective for dose-response data. The second is not much harder. Both can be done in R with nls().
Andy From: Quin Wills > > I am using "nls" to fit dose-response curves but am not sure > how to approach > more robust regression in R to get around the problem of the my error > showing increased variance with increasing dose. > > > > My understanding is that "rlm" or "lqs" would not be a good idea here. > 'Fairly new to regression work, so apologies if I'm missing something > obvious. > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
