RE: st: ml graph returns error

[B Villena <benjaminvillena@hotmail.com>]

Dear Maarten,
I have realized before that my likelihood identification was fragile. 
However, I did not know this issue may be causing trouble to compute ml graph even after a successful estimation.
 
Thank you very much for your help

Best regards,








----------------------------------------
> Date: Tue, 22 Mar 2011 08:31:10 +0000
> From: maartenbuis@yahoo.co.uk
> Subject: Re: st: ml graph returns error
> To: statalist@hsphsun2.harvard.edu
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
> --- On Mon, 21/3/11, B Villena wrote:
> > My model looks like this
> >
> > program mymod
> > args lnf xv xi phi z
> > tempvar xb
> > qui gen double `xb' = (`xv'-$xm)*(`phi'*(`xi'-$xm)+$xm-`z')
> > qui replace `lnf' =ln(normal(`xb' )) if $ML_y1==1
> > qui replace `lnf' =ln(1-normal(`xb' )) if $ML_y1==0
> > end
> >
> > where $xm is just a given constant. I checked that this model is
> > identified, in the sense that all first-order conditions are linearly
> > independent.
> >
> > Then I run my model by using ml
> >
> > ml model lf voter_lf (Xv: q = A_*, nocons) (Xi: B_*, nocons) (phi:)
> > (lambda: zs, nocons)
> >
> > where A_* is a set of saturated dummy variables, i.e. sum of all A_ add
> > up to 1; and B_* is another set of saturated dummies. Of course, A and B
> > variable sets are linearly independent, i.e.
> > if for all observations with A_j==1 there are some of them for which
> > B_k==0 and B_k==1 for all k=1,2,3,....K, and j=1,2,3,...J
> >
> > Here is the problem. If I run
> > ml model lf mymod (Xv: q = A_*, nocons) (Xi: B_*, nocons) (phi:)
> > (lambda: zs, nocons)
> > ml search
> > ml check
> > ml maximize
> > ml graph
> >
> > everything looks just fine. The model passes all 10 checks and the model
> > is estimated with sensible parameters.
> > The first problem occurs at this stage. I'm running this model many
> > times for different samples. Although I obtain the ml estimates, ml
> > graph returns an error message
> >
> > Mopt_graph_gen(): 3301 subscript invalid
> > : - function returned error
> > r(3301);
> > r(3301);
> >
> >
> > The second problem arises when I put ml check after ml search.
> > Specifically, I run
> >
> > ml model lf mymod (Xv: q = A_*, nocons) (Xi: B_*, nocons) (phi:)
> > (lambda: zs, nocons)
> > ml check
> > ml search
> > ml maximize
> > ml graph
> >
> > I get the following error
> >
> > Test 1: Calling voter_lf to check if it computes log likelihood and
> > does not alter coefficient vector...
> > opt__eval_cycle(): 3301 subscript invalid
> > opt__eval(): - function returned error
> > _optimize_evaluate(): - function returned error
> > _mopt__evaluate(): - function returned error
> > mopt__check_test1(): - function returned error
> > _moptimize_check(): - function returned error
> > Mopt_check(): - function returned error
> > : - function returned error
> > r(3301);
> > r(3301);
>
> I can see two problems:
>
> The paremeter of phi and the parameters of `xi' are
> very weakly identified, in that identification only
> seems to come from that external constant $xm. If we
> excluded that and we found some estimates for these
> parameters, and than multiplied phi by 2 and divided
> all parameters of `xi' by 2, than the likelihood
> would not change, same if we divided and multiplied
> by 2, e, 3, pi, etc. That is, in that case the model
> would not be identified. It is just that $xm is fixed
> and thus cannot be multiplied or divided that
> identification happens, but it seems to me rather
> weak and I am not surprised that computers have a
> hard time with this likelihood function.
>
>
> Second, I would replace:
> qui replace `lnf' =ln(1-normal(`xb' )) if $ML_y1==0
>
> with:
> qui replace `lnf' =ln(normal(-`xb')) if $ML_y1==0
>
> Mathematically the two statements are equivalent,
> but the latter is much easier for computers. Since
> this is already a hard problem, you need to use
> whatever trick available to make it easier for the
> computer.
>
> Hope this helps,
> Maarten
>
>
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/ 		 	   		  
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/