Dear all,
I recently use the optim function to find the maxima for some likelihood function. I have many parameters, more than 12. As the help file mention, the default method does not do well in univariate case. How about the different method in optim?
I notice the nlm function uses newton method. I have also done the newton method by myself, the iteration does not converge due to the difficulty in solve the hessian matrix for this large dimension matrix. Is the newton method worse than the method supplied in optim? In the mle package, optim is used instead of nlm.
For the different methods in optim, they give somewhat quite different estimate for some of the parameters. And the most annoying one is that the hessian matrix is sometimes not positive definite after the optim gives output using method (the default one and BFGS). Shall we admit that we have arrived at the maximum point?
For CG and SANN method, they are both very very slow, however, their maximum values are usually bigger than the default method.
Is there any suggestion in choosing these methods? I know it is a very hard optimazation question, however, I can not find the reference book in optim help at the moment. Thank you.
Yours,
Zhen
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