[R] proportional weights

[Marco Inacio]

Thanks for the answers.

> Dear Marco and Goran,
>
> Perhaps the documentation could be clearer, but it is after all a brief help page. Using weights of 2 to lm() is *not* equivalent to entering the observation twice. The weights are variance weights, not case weights.
>
According to your post here:
   http://tolstoy.newcastle.edu.au/R/e2/help/07/05/16311.html
   there are 3 possible kinds of weights.

The person in this one:
   http://tolstoy.newcastle.edu.au/R/e2/help/07/06/18743.html
   includes 2 others making a distinction between weights inverse 
proportional to variance and weight equal to inverse variance.

(looking at other posts in the thread shows that other people also make 
confusions on this matter)

So R's lm(), glm(), etc weights **are** the inverse of the variance of 
the observations, right?
They'are not **proportional** to the inverse of variance because if this 
were true, then weight and 2*weight would archive the same results, right?


I needed a method to use proportional weights on observations as I know 
their proportion of variance among each other.
And it doesn't need to be a R function, just an explanation on how 
construct the likehood would be fine. If anybody know an article on the 
subject, would be of great help to.