Hello Alecos,
In a such an exercise the "catch" command may be useful. I used it for a
bivariate estimation as follows
*loop 200 --progressive*
*do some random sorting*
*catch biprobit y1 y2 const x1 ; const x2*
*err = $error*
*if !err*
* do some stuff*
*else*
* do nothing in particular*
*endif*
*endloop*
The following link may help you
http://lists.wfu.edu/pipermail/gretl-users/2015-February/010624.html
Best,
Artur
2015-02-05 10:54 GMT+01:00 Alecos Papadopoulos <papadopalex(a)aueb.gr>:
I have to evaluate the finite-sample performance of the ML estimator
in
the estimation of a 3-parameter distribution, based on simulated samples.
The "progressive loop" environment which is set for Monte Carlo studies
does not seem to support the mle command. I ended up using the index loop
which supports the mle command, while writing the coefficient vector
obtained in each loop that is grabbed by $coeff, to successive rows of a
pre-defined zero matrix. So far so good.
The problem is the following: the distribution appears difficult to
estimate in small samples and rather often the convergence criterion for
the mle is not met (I don't mind that, this is part of the evaluation of
the performance of the MLE). But when this happens, *the loop stops. *The
total number of runs of the loop will possibly require some hours to run.
If the loop stops every time the mle does not converge, I will have to be
constantly overseeing the process for the duration, in order to re-ignite
the loop. It would be very convenient if the loop could continue
irrespective of whether the mle in a particular loop fails to converge.
Is there a way to tell Gretl not to stop the loop, even if the mle fails,
to write the container matrix with NANs, and to proceed to the next run;
Thank you.
--
Alecos Papadopoulos
Athens University of Economics and Business, Greece
Department of Economics
cell:+30-6945-378680
fax: +30-210-8259763skype:alecos.papadopoulos
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