Thank you for the suggestion of using predict!
If someone is interested here is the loop I used:
seq(0,max(subset(dati, Fiume=="Laveggio")$Portata), length=100)->seqQ
for(i in 1:35)
{
jpeg(paste("result",i,".jpg"))
plot(subset(dati,Fiume=="Laveggio")$PTG.P~subset(dati,Fiume=="Laveggio")$Portata,
main=print(formList[[i]]), sub=print(summary(resultList[[i]])$sigma))
lines(seqQ, predict(resultList[[i]], list(Portata = seqQ)))
dev.off()
}
----Messaggio originale----
Da: ssef...@gmail.com
Data: 10.02.2009 18.15
A: <lauramorg...@bluewin.ch>
Copia: <r-help@r-project.org>
Oggetto: Re: [R] plotting the result of a nonlinear regression
?predict
On Tue, Feb 10, 2009 at 11:06 AM, lauramorg...@bluewin.ch
<lauramorg...@bluewin.ch> wrote:
> Hello,
> to plot the result of a singular non linear regression (using nls) I usually
> use the function plotfit, for
example:
>
> r.PTG.V<-nls(PTG.P~ fz1(Portata, a,b), data=dati, start=list(a=10, b=10),
> nls.control(maxiter=200),
algorithm='port',
> trace=TRUE, na.action=na.omit, lower=list(a=0, b=10), upper=list(a=100,
> b=100))
> plotfit(r.PTG.V)
>
> I tried to use the function plotfit on the result of the following for loop
> but I got an error message:
> for (i in 1:length(formList))
> {
> resultList[[i]] <- nls(formList[[i]], data=subset(dati,
> Fiume=="Laveggio"), start=startList7[[i]],
> nls.control(maxiter=1000, warnOnly=TRUE), algorithm='port',
> na.action=na.omit,lower=lowerList7[[i]],
> upper=upperList7[[i]])
> }
> plotfit(resultList[[1]]
>
> "Error in diff(as.numeric(y[ord])) :
> (list) object cannot be coerced to type 'double'"
>
> Could somebody tell me what this error means? how can I fix this problem?
> Any suggestion appreciated!!
> Thanks,
> Laura
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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>
--
Stephen Sefick
Let's not spend our time and resources thinking about things that are
so little or so large that all they really do for us is puff us up and
make us feel like gods. We are mammals, and have not exhausted the
annoying little problems of being mammals.
-K. Mullis
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