confidence intervals for nls or nls2 model

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 Aut?noma de M?xico

David Winsemius, MD
West Hartford, CT