--- [email protected] wrote:
> I have run into problems with an ML estimation. I have both problems
> with "ml search" as well as with non-convergence: "ml search" simply
> cannot not find suitable initial conditions (even after specifying a
> range) and when I indicate initial conditions myself, I either get the
> error message "could not calculate numerical derivatives missing values
> encountered r(430);" or some of the parameter estimates are missing.
This happens to me all the time when I am programming a new -ml-
procedure, but it is invariably caused by me forgetting a minus sign
or multiplying things that should be added, or something like that.
I would first try to find the error in your likelihood program before
trying anything else. (It may require just putting it aside for a day)
> What I now want to do is to have loops with "ml model ...,
> init(parameter1:_cons = `a' parameter2:_cons = `b' ...) maximize" where
> I systematically go through a grid of various initial conditions
> specified as `a', `b' and so on.
>
> The problem, however, is that as soon as ml produces an error message
> (as the one above) for a given set of initial conditions, the evaluation
> of the loops is interrupted. How can I make sure, that the evaluation of
> the loops is continued even when ml produces an error message? I would
> be most grateful for any hint.
Doing a grid search like that can be useful for other reasons, but not for
the problem you sketched above. If you want to do a grid search that is
not stopped when a single call has failed to converge you can precede the
call to ml with -capture-, see: -help capture-.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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