[R] probit etc. for dose-response modeling

[ripley@stats.ox.ac.uk]

That fits by least-squares, which is not optimal.  glm fits by
maximum-likelihood.  This can matter: the menarche data set (in MASS)
is one example.

On Wed, 28 Aug 2002, Johannes Ranke wrote:

> Hi again
>
> I found that the nonlinear least squares method also works nicely:
>
> 	library(nls)
> 	model <- nls(viability ~ pnorm(-log10(conc),-EC50,slope),data=data, \
> 		 start=list(EC50=1.8,slope=0.8))
>
> Is there an advantage of using glm, and how would this work in this case?

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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