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Re: st: -xtmixed- performance problem
From
Tobias Friedli <[email protected]>
To
[email protected]
Subject
Re: st: -xtmixed- performance problem
Date
Sun, 12 Sep 2010 15:18:39 +0200
Thank you. I mainly want to deal with heteroskedasticity. Isnt there maybe a possibility to do this using the bootstrap function.
Regards
Toby
On 11.09.2010, at 17:07, Roberto G. Gutierrez, StataCorp wrote:
> Hobst <[email protected]> writes:
>
>> I want to run the following two-way error component regression in xtmixed,
>> with cluster robust standard errors
>
>> xtmixed y x1 x2 x3 x4 || _all: R.id || datevar:, mle residuals(, by(id))
>
>> Without the term residuals(,by(id)) the regression is very fast, but with
>> the the option included, it did only 2 iterations in 48h.
>
>> Does anybody have any idea, what i could do to speed the regression up? Is
>> there maybe an option to decrease accuracy or something like that?
>
> In a later post on this thread you said you have 320 groups each with 12
> observations. When you added -residuals(, by(id))- in the above you specified
> a heteroskedasticity model where you estimate a distinct residual variance for
> each group. This added 320 parameters to be estimated in your model, hence
> the slowdown.
>
> Cluster robust standard errors are currently not supported by -xtmixed-,
> although that is something we are looking into adding in the future.
>
> --Bobby
> [email protected]
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