No, you are perfectly fine using WLS. The constant of proportionality is the
estimated error variance, i.e., the square of the residual standard error
(as I think I said earlier).
John
You're right. That was a little hard for me to grasp. Thanks for the
patience.
Dear Marco,
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Marco Inacio
> Sent: Thursday, February 06, 2014 12:41 PM
> To: R help
> Subject: Re: [R] proportional weights
>
>
> > I think we ca
I think we can blame Tim Hesterberg for the confusion:
He writes
"
I'll add:
* inverse-variance weights, where var(y for observation) = 1/weight (as
opposed to just being inversely proportional to the weight) *
"
And, although I'm not a native English speaker, I think there's a spurious
c
tly clear, I'm afraid that I'll have to defer to
> someone with greater powers of explanation.
>
> Best,
> John
>
>> -Original Message-
>> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
>> project.org] On Behalf Of Marco Inacio
>> Sen
rg [mailto:r-help-bounces@r-
> project.org] On Behalf Of Marco Inacio
> Sent: Thursday, February 06, 2014 9:06 AM
> To: r-help@r-project.org
> Subject: Re: [R] proportional weights
>
> Thanks for the answers.
>
> > Dear Marco and Goran,
> >
> > Perhaps the docume
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:
Dear John,
thanks for the clarification! The lesson to be learned is that one
should be aware of the fact that weights may mean different things in
different functions, and sometimes different things in the same function
(glm)!
Göran
On 02/06/2014 02:17 PM, John Fox wrote:
Dear Marco and G
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.
You can see this by looking at the whole summary() outpu
On 05/02/14 22:40, Marco Inacio wrote:
Hello all, can help clarify something?
According to R's lm() doc:
Non-NULL weights can be used to indicate that different observations
have different variances (with the values in weights being inversely
*proportional* to the variances); or equivalently,
Hello all, can help clarify something?
According to R's lm() doc:
Non-NULL weights can be used to indicate that different observations
have different variances (with the values in weights being inversely
*proportional* to the variances); or equivalently, when the elements
of weights are positiv
10 matches
Mail list logo
