[R] R.squared in summary.lm with weights

[Duncan Murdoch]

On 07/04/2016 5:21 PM, Murray Efford wrote:
> Following some old advice on this list, I have been reading the code for summary.lm to understand the computation of R-squared from a weighted regression. Usually weights in lm are applied to squared residuals, but I see that the weighted mean of the observations is calculated as if the weights are on the original scale:
>
> [...]
>      f <- z$fitted.values
>      w <- z$weights
> [...]
>              m <- sum(w * f/sum(w))
>              [mss <-]  sum(w * (f - m)^2)
> [...]
>
> This seems inconsistent to me. What am I missing?

I think you are expecting consistency where there needn't be any.  Why 
do you see an inconsistency here?  Those are different calculations. 
You get expressions like these if you assume observations have variance 
sigma^2/w, and you're trying to estimate sigma^2.

Duncan Murdoch