Henrik Andersson <h.andersson at nioo.knaw.nl> writes:
> Do I have the right impression that it's currently not possible to
> produce confidence intervals for the nls predictions using R?
>
> I had a course were we used SAS PROC nlin and there you could get
> intervals for the parameters and the prediction but I do not have
> access to SAS.
>
> Would it be difficult to implement, I tried to dig into the help pages
> of nls, vcov and nlsModel but I could not really make sense out of
> this?
It's pretty trivial (if you stick with the linear approximation), once
you realize that predict.nls actually returns the gradient in an
attribute:
example(predict.nls)
se.fit <- sqrt(apply(attr(predict(fm,list(Time =
tt)),"gradient"),1,
function(x) sum(vcov(fm)*outer(x,x))))
matplot(tt, predict(fm,list(Time = tt))+
outer(se.fit,qnorm(c(.5, .025,.975))),type="l")
points(demand ~ Time, data = BOD)
One slight issue is that it doesn't work if "newdata" is omitted,
but
then you can easily get the gradient from fm$m$gradient()
--
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907