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:
-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 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
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Matthew C Keller Asst. Professor of Psychology University of Colorado at Boulder www.matthewckeller.com [[alternative HTML version deleted]]