Dear list,
I have an estimator I am trying to code using mata -optimize()-. During the
estimation, there are points at which I want to obtain the score matrix and
gradient vector for a specified parameter value. However, because
calculating the Hessian is computationally very intensive, I really want to
avoid computing it when it is not necessary to do so.
I had originally assumed that I could do this simply by calling
-optimize_evaluate()- followed by the appropriate -optimize_result_*()-
calls. However, it seems that -optimize_evaluate()- *does* compute the
Hessian automatically (i.e. before any subsequent call to
-optimize_result_Hessian()-).
One thing which seems to help (in terms of reducing the number of calls to
the evaluator) is to set -optimize_init_technique()- to one of the
quasi-Newton methods, such as bhhh. (This was contrary to the impression I
got from -help mf_optimize- which states that the setting of
-optimize_init_technique()- does not matter, but I guess makes sense when
you think about it.) However, this last approach still seems a bit of a
hack, I have no idea whether there is, or should be a more efficient way of
getting to just the quantities I want.
Any help or suggestions on this front would be very greatly appreciated!
Best wishes,
Glenn.
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