R help - Mar 2015 - How to decide " weight" in WLS model in R ?

Hi,

I would like to know how to decide the "weight" in a WLS model in R?

For example, In the" pipeline " data from faraway, I try to fit a
regression model Lab ~ Field (non-constant variance). I wish to use weights
to account for the non-constant variance. So how to decide the weight in
the WLS model?

For the "pipeline" data, they split the range of Field into 12 groups
of
size 9. within each group, and they compute the variance of Lab as
"varlab"
and the mean of Field as "meanfield". In addition, they suppose that
the
variance in the response is linked to the predictor in the following way:
var(Lab)=a*(Field^b).

So we could get a estimate of a and b by regress log(varlab) on
log(meanfield). But how to determine weights in a WLS fit of Lab on Field
in R?

I guess that it may require the function of 'VarConstPower' in R in the
example above. So could you please explain how to use 'VarConstPower' in
R?

I will appreciate it if you could please answer the two questions above.

Thanks!
Angela
-

	[[alternative HTML version deleted]]

Angela:

These are statistical, not R, issues I believe, and you appear to be
out of your depth statistically here. I suggest you talk to a local
statistical resource or, if you can't find such help, post on a
statistical site like stats.stackexchange.com.

Cheers,
Bert

Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374

"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll




On Mon, Mar 2, 2015 at 12:13 PM, Yan Wu <yanwu1205 at gmail.com>
wrote:
> Hi,
>
> I would like to know how to decide the "weight" in a WLS model in
R?
>
> For example, In the" pipeline " data from faraway, I try to fit a
> regression model Lab ~ Field (non-constant variance). I wish to use weights
> to account for the non-constant variance. So how to decide the weight in
> the WLS model?
>
> For the "pipeline" data, they split the range of Field into 12
groups of
> size 9. within each group, and they compute the variance of Lab as
"varlab"
> and the mean of Field as "meanfield". In addition, they suppose
that the
> variance in the response is linked to the predictor in the following way:
> var(Lab)=a*(Field^b).
>
> So we could get a estimate of a and b by regress log(varlab) on
> log(meanfield). But how to determine weights in a WLS fit of Lab on Field
> in R?
>
> I guess that it may require the function of 'VarConstPower' in R in
the
> example above. So could you please explain how to use
'VarConstPower' in R?
>
> I will appreciate it if you could please answer the two questions above.
>
> Thanks!
> Angela
> -
>
>         [[alternative HTML version deleted]]
>
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