Hi all,
I am trying to rebuild the results of a study using a different data
set. I'm using about 450 observations. The code I've written seems to
work well, but I have some troubles minimizing the negative of the
LogLikelyhood function using 5 free parameters.
As starting values I am using the result of the paper I am rebuiling.
The system.time of the calculation of the function is about 0.65 sec.
Since the free parameters should be within some boundaries I am using
the following command:
optim(fn=calculateLogLikelyhood, c(0.4, 2, 0.4, 80000, 0.8),
lower=c(0,0,0,0,0), upper=c(1, 5, Inf, Inf, 1), control=list(trace=1,
maxit=1000))
Unfortunately the result doesn't seem to be reasonable. 3 of the
optimized parameters are on the boundaries.
Unfortunately I don't have much experience using optimizatzion methods.
That's why I am asking you.
Do you have any hints for me what should be taken into account when
doing such an optimization.
Is there a good way to implement the boundaries into the code (instead
of doing it while optimizing)? I've read about parscale in the
help-section. Unfortunately I don't really know how to use it. And
anyways, could this help? What other points/controls should be taken
into account?
I know that this might be a bit little information about my current
code. But I don't know what you need to give me some advise. Just let me
know what you need to know.
Thankds
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