Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: -xtmixed- performance problem

From (Roberto G. Gutierrez, StataCorp)
Subject   Re: st: -xtmixed- performance problem
Date   Sat, 11 Sep 2010 10:07:59 -0500

Hobst <> 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: || 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.

*   For searches and help try:

© Copyright 1996–2015 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index