> Hi,
>
> I am having difficulty successfully setting up a bivariate
> sire model with one (0,1) trait (stay) and one normally distributed
> trait (pba1).
>
> I suspect it is in the variance structures I am going wrong, but
> the ordering of the model line also makes a difference
> (ie stay !BIN !LOG pba1 ~......
> stay pba1 !BIN !LOG ~......)
The latter form is what I use in my test example.
It is probable that the former form looses the pba1 string when
processing the qualifiers. I.e. ASREML blanks each option as it reads
it and probably blanks the pba1 out too.
>
> I get various problems - eg unable to invert R or G, likelihood diverging
> - depending on how I set up the R structure. It also doesn't seem to "see"
> the Tr.sire, only appearing to have one component for it when I can get it
> to run that far.
>
> The .as file follows. Any help greatly appreciated.
>
> Ron.
>
>
> Stayability to parity 3
> sow
> sire !P
> stay
> fa
> pbd1 pbdl
> avpba avpbd
> fgl 2
> pba1 pba2 pba3
> fg1 2 fg2 2 fg3 2
> pedig.mgs !MGS
> two.dat
> stay pba1 !BIN !LOG ~ -Trait Tr.fa !r Tr.sire !f Tr.fg1
> 1 2 1
> 0
> Tr 0 US 1 0 5.0
> Tr.sire 2
> Tr 0 US 0.1 0 0.7
> sire
>
>
I can't see anything wrong with this coding. Does it fail on the first
iteration or after some? I suggest you do the two univariate
analyses first. Then do a bivariate with correlations fixed to
zero !GPFP and then relax to estimate the correlations.
If you want to estimate the correlation, best not to start it at zero.
Arthur
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Arthur Gilmour PhD mailto:Arthur.Gilmour@agric.nsw.gov.au
Principal Research Scientist (Biometrics) fax: <61> 2 6391 3899
NSW Agriculture <61> 2 6391 3922
Orange Agricultural Institute telephone work: <61> 2 6391 3815
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