[R] confidence intervals for nls or nls2 model

[Francisco Mora Ardila]

Hi all

I have fitted a model usinf nls function to these data:

> x
 [1]   1   0   0   4   3   5  12  10  12 100 100 100

> y
 [1]  1.281055090  1.563609934  0.001570796  2.291579783  0.841891853
 [6]  6.553951324 14.243274230 14.519899320 15.066473610 21.728809880
[11] 18.553054450 23.722637370

The model fitted is:

modellogis<-nls(y~SSlogis(x,a,b,c))

It runs OK. Then I calculate confidence intervals for the actual data using:

dataci<-predict(as.lm(modellogis), interval = "confidence")

BUt I don´t get smooth curves when plotting it, so I want to get other "confidence 
vectors" based on a new x vector by defining a new data to do predictions:

x0 <-  seq(0,15,1)
dataci<-predict(as.lm(modellogis), newdata=data.frame(x=x0), interval = "confidence")

BUt it does not work: I get the same initial confidence interval

Any ideas on how to get tconfidence and prediction intervals using new X data on a 
previous model?

Thanks 

Francisco



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Francisco Mora Ardila
Estudiante de Doctorado
Centro de Investigaciones en Ecosistemas
Universidad Nacional Autónoma de México