Dave,
it is much more efficient to fit a sire-mgs model using the 'overlay'
option, rather than using the ASREML build-in facility (which transforms it
into an animal model when I understood correctly). To overlay mgs with sire
your model would become:
prot% ~ mu season period sea.per jersey het cowage region,
!r sire 0.207 -mgs and(mgs,0.5) 0.05 key 1.003 locn 2.066
and omit the !MGS on the pedigree file name. That should work similarly fast
as the plain sire model.
Luc.
Dr. Luc Janss, Scientist Quantitative Genetics
ID-Lelystad Institute for Animal Science and Health
P.O. Box 65 Tel. +31.320.23.82.59
8200 AB Lelystad, The Netherlands Fax. +31.320.23.80.50
L.L.G.Janss@id.wag-ur.nl !! NEW EMAIL
> -----Original Message-----
> From: Dave Johnson [SMTP:djohnson@lic.co.nz]
> Sent: Friday, August 11, 2000 3:04 AM
> To: asreml@chiswick.anprod.csiro.au
> Subject:
>
> Thanks to earlier responses I have the sire model working and it took
> about 10
> minutes per iteration. I then added the maternal grandsire (same factor as
> sire,
> ~10800 levels) without fitting the covariance and it seems to be
> converging but
> taking about 1 day per iteration. I also had to increase memory at least
> 4-fold
> (-s5 to -s7). I'm puzzled at the great increase in memory and time - am I
> expecting too much of this model? The mgs factor has some missings and
> I'm not
> sure what the program does with those records? Thanks.
>
> Region comparison of concentrations
> key 106031 !I
> region 6
> jersey !/16
> het
> sire !P
> mgs !M0 !P
> locn 14105
> season 11 !I
> period 3
> cowage 4 !I
> dim
> logdim
> pro_fat
> fat%
> prot%
> ped.txt !MGS
> regions.txt
> prot% ~ mu season period sea.per jersey het cowage region,
> !r sire 0.207 mgs 0.05 key 1.003 locn 2.066
>
>
>
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