estimating variance components for arbitrarily defined var/covar matrices

Hi all,

This has been wonderful to follow, thank you very much to all who have
contributed!!

Quick clarification:
Z*Z' is fixed/known. VG is unknown and would be estimated from the data.

Another issue:
The number of individuals fit in these models is often very large (e.g.,
10K - 100K) because the variance of the off-diagonals of Z*Z' is tiny. Of
the above approaches suggested, are any able to work with datasets of this
size in a 'reasonable' amount of time? E.g., < 1 day?

Best,

Matt

On Thu, Feb 26, 2015 at 2:47 PM, Rolf Turner <r.turner at auckland.ac.nz>
wrote:

On 26/02/15 16:54, Ben Bolker wrote:

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   I thought we were assuming a fixed var-cov matrix

So Z*Z'*VG is fixed/known, rather than being estimated from the data.

That's what I didn't properly apprehend.

 PLUS an error

variance, i.e. Sigma + s^2*I (increasing the variance and decreasing
the correlation).

   But I could be wrong about what model is intended.

No, I think that the misunderstanding was entirely mine.

Sorry for the noise.

cheers,

Rolf

--
Rolf Turner
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
Home phone: +64-9-480-4619

--
Matthew C Keller
Asst. Professor of Psychology
University of Colorado at Boulder
www.matthewckeller.com

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