Hi all,
Fitting tri-variate models with CIs but CIs look odd.
They are to close to the point estimate and lower point is sometimes higher that point estimate.
Below a selection
MZMmodel.sdAm[1,1] 3.224423e-01 0.32244499 0.39122315
MZMmodel.sdAm[1,2] 4.477139e-01 0.58554106 0.58555366
MZMmodel.sdAm[1,3] 8.285475e-01 0.82850806 0.82855803
MZMmodel.sdAm[2,1] 4.477139e-01 0.58554106 0.58555366
MZMmodel.sdAm[2,2] 4.104425e-01 0.41044353 0.41043733
MZMmodel.sdAm[2,3] 4.554080e-01 0.45540625 0.61216648
MZMmodel.sdAm[3,1] 8.285475e-01 0.82850806 0.82855803
MZMmodel.sdAm[3,2] 4.554080e-01 0.45540625 0.61216648
MZMmodel.sdAm[3,3] 4.554037e-01 0.45540226 0.52462605
MZMmodel.sdCm[1,1] 5.278062e-15 0.01168100 0.07729734
Any suggestions what might cause the problem? (and solution to solve it?)
thanks
Meike
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I would try changing the function precision; 1.e-12 might be better for continuous data, probably best not to go much lower, how's this look?
CholACEFit@optionslist()
(so nothing specific set for this model)... Check the system setting (probably the defaults)
[1] "1e-14"
Ok let's make it a bit less accurate (this will force larger step-sizes during estimates of the gradients which the optimizer had incorrectly estimated to be zero) and then re-run it
snip snip...
confidence intervals:
lbound estimate ubound
MZMmodel.sdAm[1,1] 0.2835146 0.3395857 0.3941184
MZMmodel.sdAm[1,2] 0.6855848 0.8962901 1.1197032
MZMmodel.sdAm[2,1] 0.6855848 0.8962901 1.1197032
MZMmodel.sdAm[2,2] 0.4117450 0.4652302 0.5155276