[ADMB Users] difference between ADMB-RE and R/mgcv in SEs for smoother coefficients in a GAM fitted by maximum likelihood
dave fournier
davef at otter-rsch.com
Thu Nov 29 09:53:01 PST 2012
A very simple example shows how the method works.
DATA_SECTION
PARAMETER_SECTION
init_number x
random_effects_vector u(1,1)
objective_function_value f
sdreport_number sd1
sdreport_number sd2
PROCEDURE_SECTION
f= square(x-10) + 0.5*square(u(1)) + square(u(1)-x);
sd1=u(1)-x;
sd2=x-u(1);
The logarithm of the determinant of the hessian = 0.980829
index name value std.dev 1 2 3
1 x 7.5002e+00 6.1237e-01 1.0000
2 u 5.0001e+00 5.7735e-01 0.0000 1.0000
3 sd1 -2.5001e+00 8.4163e-01 -0.7276 0.6860 1.0000
4 sd2 2.5001e+00 8.4163e-01 0.7276 -0.6860 -1.0000 1.0000
I guess the question is whether this is reasonable for sd1. It seems a
bit large to me.
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