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Re: st: -xtmixed- performance problem


From   Tobias Friedli <tobias.friedli@access.uzh.ch>
To   statalist@hsphsun2.harvard.edu
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 <tobias.friedli@access.uzh.ch> 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
> rgutierrez@stata.com
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