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?
Thanks for your consideration.
School of Land and Food,
Uni of QLD
St Lucia 4072, QLD