Spatial correlations and measurment (nugget) variance

Dear ASReml List
I am wondering what your thoughts on the units term (measurement error)
for a multi-environment crop trial are. Specifically, it seems to me that
the measurement error variance can differ across environments (we have
different people taking measurements in different places in many cases).
So, it makes sense to model separate units variances across locations.
But, my model is already huge and execution times with a single units
variance plus heterogeneous AR1 x AR1 error structures is already pushing
the limits of estimability. So, I have not yet tried a heterogeneous
units model, but I am wondering if, in the case that it is too complex,
does it make more sense to include a common homogenous units variance in
the model or instead drop it and allow the measurement variance to be
incorporated back into the heterogeneous AR1 x AR1 error structures? If
the units variance really is heterogeneous, would dropping the units
variance be better than trying to model a common variance?

Thanks for any insight you can provide. Regards - Jim

Jim Holland ("Holland, Jim" <Jim.Holland_at_ARS.USDA.GOV>)
USDA-ARS Plant Science Research Unit
Department of Crop Science
North Carolina State University
Phone: 919-513-4198
Fax: 919-515-7959
Web: http://www4.ncsu.edu/~jholland/homepage.htm

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Received on Tue Aug 31 2007 - 11:09:16 EST