Thanks Jack. Faster than gretl, as usual.
Alecos Papadopoulos PhD Athens University of Economics and Business web: alecospapadopoulos.wordpress.com/ skype:alecos.papadopoulos
On Thu, 26 Mar 2020, Alecos Papadopoulos wrote:
Gretl 2020a windows 64bit.
Consider the following output from mle estimation (pay attention to the Gradient values and the NA std errors):
[...]
I have a question, and a suspicion about what the answer might be.
My question is: since the Std errors are based on the Outer Products matrix, why are they not computed/presented ? Never mind whether this is a successful estimation attempt -it is not. My question is "mechanical". I would understand "NA" if I was asking for std errors based on the inverted Hessian. But where is the problem in computing std errors based on the gradient?
Your suspicion, I suspect, is just slightly off the mark. The OPG matrix is in fact calculated as G'G, banking on the idea that sumc(G) should be 0 at convergence (note: differently from your message, here I'm using G for the n x k matrix of gradients per observation). The name you gave to the coefficients seem to suggest that you have a variance parameter whose estimate is numerically 0. In those cases, it wouldn't surprise me if the G'G matrix (which is positive semidefinite by construction) was numerically singular; upon inversion, God knows what could happen. For all we know, it could be full of negative elements.
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Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Universitą Politecnica delle Marche
(formerly known as Universitą di Ancona)
r.lucchetti@univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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