Thank you very much for your answer.
> First off, why do you want to write your own program when Stata
> already has one? Even if you get your program to work, Stata's will
> likely be quicker, more efficient and less likely to encounter problems.
I am working on a more structural model that restricts the way the
threshold/cutoff points are calculated. So, writing up a program which is
identical to oprobit, is just the first step to my work.
> Second, while you may have the formulas right, that doesn't mean your
> code is the same as oprobit's. The programs go through an iterative
> procedure, and some procedures will work better than others.
In fact, I am really concerned about this iteration procedures, as the
estimates on some of my dummy variables are a lot different depending on
the tolerance levels.
> Try adding the difficult option to your ml maximize commands, e.g.
> ml maximize, difficult
> According to the help, "difficult specifies that a different stepping
> algorithm be used in nonconcave regions. There is no
> guarantee that difficult will work better than the default; sometimes
> it is better, and sometimes it is worse. You should use the
> difficult option only when the default stepper declares convergence
> and the last iteration is "not concave", or when the default
> stepper is repeatedly issuing "not concave" messages and
> only producing tiny improvements in the log likelihood."
>
> You could also try playing around with the technique option. Type
> -help maximize- for more details.
I tried "difficult" as well and from "maximize" help, the only two that
are clearly stated are tolerance and Itorelance levels, which I already
played around with.
I found "oprobit.ado" file from stata now and am gonna try to depuzzle
it. Thank you very much again...
Sunhwa
**************************************
Lee, Sunhwa
PhD Candidate
Department of Economics
University of California at Davis
Davis, CA, 95616
(Office) 109 SSH
(Phone) (530)752-2845
**************************************
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