On Feb 19, 2013, at 5:25 PM, Malikov, Emir wrote:
> Hello --
>
> The question I have is about the gmm() function from the 'gmm' package
> (v. 1.4-5).
>
> The manual accompanying the package says that the gmm() function is
> programmed to use either of four numerical solvers -- optim, optimize,
> constrOptim, or nlminb -- for the minimization of the GMM objective
> function.
>
> I wonder whether there is a way to pass controls to a solver used
> while calling the gmm() function?
>
> In particular, the problem that I have been having is that the gmm()
> fails to converge withing the default number of iteration for the
> 'optim' solver that it uses. Ideally, I would wish to figure out a way
> to be able to choose controls, including the number of iterations, for
> the solver that I tell gmm() to use.
>
> Currently, the way I call the function is as follows:
>
> model.name <- gmm(g=g.fn, x=data, gradv=g.gr, t0=c(start),
> type=c("twostep"), optfct=c("optim") )
>
> I also would want the gmm() function to know that I want it to pass
> the following control -- maxit=1500 -- to the optim solver.
The argument name in the manual is `itermax`. I cannot tell from lookng at the
code whether that would get passed to 'optim'.
> Unfortunately, the 'gmm' manual does not tell whether this is doable.
There is also a "..." argument which is stated in the help page to be passed
to "optim". Looking at ?optim one sees that controls generally need to be in a
list named 'control'. That this is the intent is supported by the sentence on
page 11 of the gmm vignette:
"We could try di erent starting values, increase the number of iterations in
the control option of
optim or use nlminb which allows to put restrictions on the parameter space."
--
David Winsemius
Alameda, CA, USA
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