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st: gf type evaluator

From   Klaus Pforr <>
Subject   st: gf type evaluator
Date   Sat, 13 Nov 2010 16:13:47 +0100

Dear Listers,

I'm working on ml evaluator for panel data and have a question about the gf2 type evaluator in moptimize. The manual and help files say that gf has to produce the group-level likelihood, the group-level scores and the hessian. I'm confused about the scores, as the manual says that the score matrix is supposed to be a matrix L x K, with L being the number of independent elements, i.e. the groups, and K being the number of coefficients. Does S really expect the derivative with respect to the parameters, i.e. the linear combinations for each equation, or the actually the derivatives with respect to the beta coefficients. If the first is true, I do not understand how I implement observation level scores with a likelihood that is only defined at the group level.

kind regards



Klaus Pforr
Universität Mannheim
D - 68131 Mannheim
Tel:  +49-621-181 2801
fax:  +49-621-181 2803

Besucheranschrift: A5, Raum A312

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