[R] gnls or nlme : how to obtain confidence intervals of fitted values

[Andrew Robinson]

The function estimable() from the gmodels part of the gregmisc package
will do this, if applied appropriately.

It allows for the estimation of arbitrary linear combinations of the
parameter estimates of a model object, and calcualtes confidence
intervals.

I hope that this helps,

Andrew



On Tue, Oct 05, 2004 at 12:31:48AM +1300, David Scott wrote:
> On Mon, 4 Oct 2004, Pierre MONTPIED wrote:
> 
> >Thanks Spencer but the intervals function gives confidence intervals of 
> >the parameters of the model not the predicted values. In the Soybean 
> >example it would be the CI of predicted weight for a given time, knowing 
> >all the parameters (Asym, xmid, scal, variance function and residual) and 
> >their distributions.
> >
> >And what I need to calculate is precisely this CI.
> >
> >My question is therefore is there an analytical way to calculate such CI, 
> >whatever the model, or could I try some randomizing techniques such as 
> >bootstrap or other ?
> >
> 
> I find I have a need for this too but for the fixed effects in a mixed 
> model fitted with lme. I have fitted a polynomial to some longitudinal 
> data, plus some other fixed effects and some random effects. I can use 
> predict to get the fitted polynomial for particular values of the other 
> predictors, but I would really like to put some confidence bounds on it. I 
> am not wild about bootstrapping---just fitting the model can take 30 
> minutes.
> 
> Any suggestions will be gratefully received (although on second thoughts 
> if someone tells me to use SAS I will be less than grateful).
> 
> David Scott
> 
> 
> 
> _________________________________________________________________
> David Scott	Department of Statistics, Tamaki Campus
> 		The University of Auckland, PB 92019
> 		Auckland	NEW ZEALAND
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> 
> 
> Graduate Officer, Department of Statistics
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