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
______________________________________________
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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.
