If you are looking for a parameteric form then a polynomial seems
to work:
plot(delta ~ ph)
for(i in 1:4) lines(ph, fitted(lm(delta ~ poly(ph, i))), col = i, lty = i)
legend("topright", legend = 1:4, col = 1:4, lty = 1:4)
On Thu, Nov 20, 2008 at 6:53 AM, Dani Valverde <[EMAIL PROTECTED]> wrote:
> 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
>
> --
> Daniel Valverde Saubí
>
> Grup de Biologia Molecular de Llevats
> Facultat de Veterinària de la Universitat Autònoma de Barcelona
> Edifici V, Campus UAB
> 08193 Cerdanyola del Vallès- SPAIN
>
> Centro de Investigación Biomédica en Red
> en Bioingeniería, Biomateriales y
> Nanomedicina (CIBER-BBN)
>
> Grup d'Aplicacions Biomèdiques de la RMN
> Facultat de Biociències
> Universitat Autònoma de Barcelona
> Edifici Cs, Campus UAB
> 08193 Cerdanyola del Vallès- SPAIN
> +34 93 5814126
>
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