[R] confidence intervals for nls or nls2 model

[David Winsemius]

On May 15, 2012, at 8:08 PM, Francisco Mora Ardila wrote:

> 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 am really getting tired of seeing the phrase "doesn't work". And on  
my machine it throws an error saying there is no as.lm function> This  
seemes to give "smooth results:

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

And notice that this message is in ?predict.nls

interval
"At present this argument is ignored.

> 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
>
>
>
> ----------------------
> Francisco Mora Ardila
> Estudiante de Doctorado
> Centro de Investigaciones en Ecosistemas
> Universidad Nacional Autónoma de México
>
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David Winsemius, MD
West Hartford, CT