Hi all,
Further to Brians comment last week:
>
> Hi there,
>
> I understand that if you want to fit a random spline row, you must fit a
> fixed linear row in the model as well. So what is the difference between the
> following two models:
>
> Model (1) yield ~ lin(row) genotype !r spl(lin(row))
> Model (2) yield ~ lin(row) genotype !r spl(row)
>
> I found in some of the wheat variety trials I analyzed, fitting Model (1)
> caused a problem "Insufficient points for spl(lin(row))", while fitting
> Model (2) worked well. Is this due to the lack of degree of freedom for
> Model (1) and how is the degree of freedom estimated ? Could we just simply
> use Model (2) in this case?
ASREML cannot interpret doubly nested terms like spl(lin(row))
at present. The simple form spl(row) does the right thing - it always
uses 'row' as a variate even if it is declared as a factor (since
a variate is always required).
>
> Thanks for your consideration.
>
>
> Chungui
> Chungui Qiao
> School of Land and Food,
> Uni of QLD
> St Lucia 4072, QLD
> Ph: (07)33652859
> Fax:(07)33651177
>
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Arthur Gilmour PhD email: Arthur.Gilmour@agric.nsw.gov.au
Senior 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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