[R] nlme weighted

[Dieter Menne]

Mollet, Fabian <Fabian.Mollet <at> wur.nl> writes:

> I'm fitting a non linear model (energy allocation model to individual
> growth data) using your nlme routine. For each individual I have thus a
> number of observations (age and size) to which I fit the nonlinear
> function, with random effects for the individuals on the estimated
> parameters (individual as the grouping factor). The sampling of these
...
> I think what I need is something that multiplies these weights to the
> residual variance. My first hint would be something as it is described
> by the function varIdent or varFixed, but it is not quite clear to me
> what is being done by these (e.g. what is meant by variance covariate
> etc.?).

In most other R regression packages, most notably lm, weights works 
the way you think it should, but the philosophy is different in lme, 
where a function is executed to compute weights, for example to 
handle heteroscedasticity.

I found this strange in the beginning, but as often Douglas Bates has 
a hidden agenda telling his users: don't do that. Don't average first 
and it later, use the raw data instead, and all the weights will be 
correct. And use the liberated parameter for more important things.

Dieter