Hi,
I'm starting to use the predict statement, but I'm not sure about how
does it work. Using a model like:
!part 13
PPY ~ mu subrace rep !r mother
0
predict subrace
I obtain results for subraces like:
rep is averaged over fixed levels
Predicted values of PPY
mother is ignored in the prediction
WARNING: Missing cells in table
subrace Predicted_Value Standard_Error EPcode
"Flinders Island" 51.1017 0.4593 P
"King Island" 51.7799 0.4051 P
"Strzelecki Ranges" 51.2644 0.4696 P
"Southern Tasmania" 52.0033 0.4782 P
"Western Otways" 52.2484 0.4108 P
"North-eastern Tasma 50.5914 0.6675 P
"South-eastern Tasma 51.9727 0.3643 P
"Strzelecki Foothill 50.7930 0.4653 P
Standard Error of Difference: Min 0.5433 Mean 0.6613 Max 0.8188
From the as file mu is 50.4851 with sdterr 0.490574. Shouldn't some of
the subrace solutions be over and some under the overall mean? That is
the case if I calculate mu+subrace effects (either from the .asr or
the .sln files). I would appreciate an explanation about how does
predict work.
Best regards,
Luis
--
Dr Luis A. Apiolaza
Quantitative Geneticist
CRC for Sustainable Production Forestry
School of Plant Science
University of Tasmania
GPO Box 252-55
Hobart TAS 7001
Australia
phone: +61-3-6226 2213
fax: +61-3-9229 2698
email: mailto:luis.apiolaza@utas.edu.au
'The search for truth is more precious than
its possession' --Albert Einstein
http://www.scieng.utas.edu.au/plantsci/http://www.geocities.com/uncronopio/
;-)
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