Re: [R] How to get around heteroscedasticity with non-linear leas t squares in R?

From: Peter Dalgaard <p.dalgaard_at_biostat.ku.dk>
Date: Wed 22 Feb 2006 - 07:28:14 EST

"Liaw, Andy" <andy_liaw@merck.com> writes:

> 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().

And there is gnls() which allows direct modelling of the variance.

        -p  

> 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]]
> >
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-- 
   O__  ---- Peter Dalgaard             ุster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
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Received on Wed Feb 22 08:53:39 2006

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