Hello,

I find your recommended procedure not very sensible but:

a) sum(fit$residuals^2)/fit|$d||f.residual
|
b) This is a statistical question but, for instance, in the case of 
repeated mesures. But you'd use the precision (1/variance) of the 
original data, computed by groups of regressor.

Hope this helps,

Rui Barradas

Em 13-10-2012 20:07, Eiko Fried escreveu:
> Hello.
>
> I'm am trying to follow a recommendation to deal with a dependent variable
> in a linear regression.
>
> I read that, due to the positive trend in my dependent variable residual vs
> mean function, I should
> 1) run a linear regression to estimate the standard deviations from this
> trend, and
> 2) run a second linear regression and use 1 / variance as weight.
>
> These might be terribly stupid questions, but:
> a) Where do I find the standard deviations from this trend in the lm
> output? Except for coefficients I only see residual std error, DF, R^2, F
> and p values.
> b) Why exactly does one adjust a linear regression by a 1/variance weight,
> and in what cases?
>
> Thanks
> T
>
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