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 Saub? Grup de Biologia Molecular de Llevats Facultat de Veterin?ria de la Universitat Aut?noma de Barcelona Edifici V, Campus UAB 08193 Cerdanyola del Vall?s- SPAIN Centro de Investigaci?n Biom?dica en Red en Bioingenier?a, Biomateriales y Nanomedicina (CIBER-BBN) Grup d'Aplicacions Biom?diques de la RMN Facultat de Bioci?ncies Universitat Aut?noma de Barcelona Edifici Cs, Campus UAB 08193 Cerdanyola del Vall?s- SPAIN +34 93 5814126
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 <daniel.valverde at
uab.cat> 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 Saub?
>
> Grup de Biologia Molecular de Llevats
> Facultat de Veterin?ria de la Universitat Aut?noma de Barcelona
> Edifici V, Campus UAB
> 08193 Cerdanyola del Vall?s- SPAIN
>
> Centro de Investigaci?n Biom?dica en Red
> en Bioingenier?a, Biomateriales y
> Nanomedicina (CIBER-BBN)
>
> Grup d'Aplicacions Biom?diques de la RMN
> Facultat de Bioci?ncies
> Universitat Aut?noma de Barcelona
> Edifici Cs, Campus UAB
> 08193 Cerdanyola del Vall?s- SPAIN
> +34 93 5814126
>
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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 f?r Medizinische Biometrie und Epidemiologie Universit?tsklinikum Hamburg-Eppendorf Martinistr. 52 20246 Hamburg T ++49/40/42803-8243 F ++49/40/42803-7790