Dear Dorte,
I suspect ASReml is ignoring the weights. The first thing to check
is whether you get the same results if you either drop the !wt qualifier,
or rescale it (say double it).
ASReml could handle weights in direct product with the variance matrix
(i.e. same weight for both traits within a unit)
but as you indicate, it is not obvious how to incorprate individual
weights which differ between traits.
<><><><><><><><><><><><><><><><><><><><><><><><><>
Wittenburg, Dörte <wittenburg_at_FBN-DUMMERSTORF.DE>
Sent by: ASReml users discussion group <ASREML-L_at_AGRIC.NSW.GOV.AU>
21/08/2007 06:52 PM
Please respond to ASReml users discussion group
To: ASREML-L_at_AGRIC.NSW.GOV.AU
cc:
Subject: weighted bivariate analysis
Hi,
I am trying a weighted bivariate analysis with data that are prepared in a
univariate way. For the two traits I have generated different weights, w1
and w2. ASReml 2.0 works fine. Now my question is, how does the residual
covariance structure looks like when I define the R structure as "I times
US" ? If I use the notation units within traits (US times I), then I think
it is
Cov(e1,e2)=( sigma_e1^2*diag(w1){-1}, rho*sigma_e1*sigma_e2*I )
( rho*sigma_e1*sigma_e2*I, sigma_e2^2*diag(w2){-1} )
Am I right?
My .asr file:
Bivariate analysis
mmutter !A !P
dam !A !P
gewicht
log_var
sau * !I
vater !A
paritaet 4
saison * !I
merkmal 2
sort_pedigree.ped !SKIP 1 !ALPHA !MAKE
data_univariat_w.asd !SKIP 1 !MAXIT 200 !DOPART $1 !ASMV 2
!TYPEIIISS
!PART 1
log_var !WT gewicht ~ merkmal merkmal.paritaet at(merkmal,1).saison,
!r ![ merkmal.mmutter at(merkmal,2).dam !] at(merkmal,1).vater
at(merkmal,1).sau !f mv
1 2 1
0 0 IDV
merkmal 0 US
1 -0.5 18
merkmal.mmutter 2
3 0 US 1 0.1 1 0.1 0.2 1 !GP
0 0 AINV
Many thanks for response,
Dörte Wittenburg
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
FBN Dummerstorf
Genetik & Biometrie
Wilhelm-Stahl-Allee 2
18196 Dummerstorf, Germany
email wittenburg_at_fbn-dummerstorf.de
phone +4938208 68-931
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Received on Sun Aug 22 2007 - 15:53:35 EST
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