nlme Fixed Variance Function

Agostino Moro <agostino.moro99 at ...> writes:

Dear R users,

I am trying to fit a gls model and weight my data points using a
VarFixed structure. I have found many examples, but I do not
understand the difference between the following models with varFixed
specified in a different way:

mod<-gls(y~x,weights=varFixed(~1/invsigma)

mod<-gls(y~x,weights=varFixed(~invsigma)

In my case I would simply like to weigh my data points by their
inverse variance.

It would be interesting to have links to examples that show
these two usages.  One of them must be wrong, or at least weird.
Have you looked at ?varFixed?  It says:

 Letting v denote the variance covariate defined in ?value?, the variance
     function s2(v) for this class is s2(v)=|v|. 

Thus if you know the variance _a priori_ is 'yvar' I think you want
weights=varFixed(~yvar) .  This will set the variance to yvar and
hence weight by 1/yvar.  (I'm using "yvar" rather than "sigma" or
"invsigma" because it's easy to get confused about whether "sigma"
represents variance or standard deviation ...)

  I would strongly recommend using the 'data' argument: have x, y, 
and yvar as columns in a data frame d and use

mod <- gls(y~x,weights=varFixed(~yvar),data=d)

  Taking a look at Pinheiro and Bates 2000 would be a good idea.
If you're too cheap or in too much of a hurry to buy it, you can
search for "varFixed" within the book on Google books (see p. 209)
for a slightly more extended discussion of the admittedly terse
example in ?varFixed ...