how do I predict across regions and deal with aliasing and nesting in ASREML-R?

From: Scott Chapman <Scott.Chapman_at_CSIRO.AU>
Date: Mon, 25 Feb 2008 16:22:58 +1000

On the bottom of page 65 of the ASREML-R manual (release 2.0, Feb 2007),
there is this text:
"The present argument enables the construction of means by averaging
only the estimable cells of the hyper-table. It is reguarly used for
nested factors, for example locations nested in regions."
Unfortunately, there is no example....
I have some across region analyses of crop genotype (G) data with BLUEs
and weights as input. I wish to estimate the hyper-table of Region x
 Has anyone got some examples of models/predictions using the present
argument to do this? Whatever model I use in ASREML-R I usually end up
with 'aliasing' and therefore a set of NAs for my predictions. I can
override the aliasing, but am afraid that I might be overfitting in any
case.... Some of the models I've tried are:
Fixed = Env, random = ~ G + Reg:G + Reg:Env:G
Fixed = Env, random = ~ corh(Reg):G
Fixed = Env, random = ~ diag(Reg):G + diag(Env):G Am not sure if this
one is legit - am assuming that the regional interaction will be taken
out first... Unless there is some way to nest it within regions...?

Scott Chapman
Principal Research Scientist
Crop Adaptation
CSIRO Plant Industry
Queensland Bioscience Precinct, 306 Carmody Rd, St. Lucia, QLD 4067,
Ph: +61 7 3214 2254 Fax: +61 7 3214 2920 Web:

Received on Thu Feb 25 2008 - 16:22:58 EST

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