[R-sig-ME] estimating variance components for arbitrarily defined var/covar matrices

Matthew Keller mckellercran at gmail.com
Thu Feb 26 23:05:34 CET 2015

Hi all,

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

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?



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

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

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