[R] Fitting a model

[Eik Vettorazzi]

you might use the drc-package (equivalently you could use nls with an 
appropriate "selfstart" model like SSlogis)

library(drc)
mm<-drm(delta~ph,fct=LL.4())
plot(mm)

 From your plot I was assuming that "ph" is the independent variable (as 
modelled above) - so if you want to predict a ph from delta you will 
need the "inverse" function of your fitted model -  you could toy with 
ED from the drc package or do a simple grid search with "predict".

hth.


Dani Valverde schrieb:
> Hello,
> This is a very basic question, but I don'y know the answer. I have 
> these data
>
> delta <- 
> c(28.6-8.825,28.6-8.828,28.6-8.836,28.6-8.845,28.6-8.897,28.6-8.944,28.6-9.027,28.6-9.091,28.6-9.263,28.6-9.4,28.6-9.7,28.6-9.981, 
>
> 28.6-10.287,28.6-10.48,28.6-10.684,28.6-10.875)
> ph <- c(4.4,4.6,4.8,5,5.2,5.4,5.6,5.8,6,6.2,6.4,6.6,6.8,7,7.2,7.4)
> plot(ph,delta,ylab=c(expression(Delta*delta)),xlab="pH")
>
> Which kind of model can I fit on these, so that can I predict for a 
> given delta the pH of my sample? Once the model is fitted, how can I 
> plot it on the graph?
> Best regards,
>
> Dani
>

-- 
Eik Vettorazzi
Institut für Medizinische Biometrie und Epidemiologie
Universitätsklinikum Hamburg-Eppendorf

Martinistr. 52
20246 Hamburg

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