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st: Maximising likelihoods that do not meet the linear-form restrictions


From   "Arne Risa Hole" <arnehole@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Maximising likelihoods that do not meet the linear-form restrictions
Date   Fri, 4 Aug 2006 11:53:02 +0100

Dear all

I was wondering if anyone knows whether StataCorp has considered
extending the functionality of the -ml- command to allow the
alternative optimisation algorithms (BHHH etc) to be used to maximise
likelihoods that do not meet the linear-form restrictions.

My understanding is that at the moment the only way these algorithms
can be used is to pass the equation scores to -ml- as g1, g2 etc. and
that this only works if each observation contains a score.

One useful extension would be to allow the possibility of passing the
values of the likelihood differentiated with respect to the
coefficients (instead of the equations/ index functions) directly to
-ml-. Then the observations containing the scores for the groups of
observations could be identified using "if==`last'", or something
similar.

I have used this approach along with matrix accum to create the outer
product of gradient matrix. Setting `negH' equal to this matrix
produces a "homemade" BHHH procedure which seems to work fine, but it
would be nice to also be able to use the other algorithms.

There might be good reasons for this not being possible but any
thoughts would be much appreciated.

Thanks
Arne
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