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

From: Berton Gunter <gunter.berton_at_gene.com>
Date: Thu 23 Feb 2006 - 03:23:26 EST


And an added US$.02 is that the raw response (optical density, counts (large numbers) of radio decay, fluorescence units, etc.) in dose response curves often varies over several orders of magnitude, so that, in conformance to John Tukey's "First Aid" suggestions, a log transformation or something similar is often a standard prescription for fitting dose/response curves (with the usual handwringing about whether the error is additive or multiplicative; there is typically some of both, as David Rocke's papers of a decade or more ago argue).

"The business of the statistician is to catalyze the scientific learning process." - George E. P. Box    

> -----Original Message-----
> From: r-help-bounces@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Christian Ritz
> Sent: Wednesday, February 22, 2006 1:22 AM
> To: quin.wills@googlemail.com
> Cc: r-help@stat.math.ethz.ch; p.dalgaard@biostat.ku.dk
> Subject: Re: [R] How to get around heteroscedasticity with
> non-linear leastsquares in R?
>
> Hi Quin,
>
> the package 'drc' on CRAN deals with modelling dose-response curves.
>
> Moreover it allows adjustment for heterogeneity by means of
>
>
> transformation (Box-Cox transformation)
>
> modelling the variance as a power of the mean.
>
>
> See the package documentation for more features.
>
>
> Christian
>
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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Feb 23 03:55:09 2006

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