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Re: st: Non-convergence in a ZIP model

From   Joseph Coveney <[email protected]>
To   Statalist <[email protected]>
Subject   Re: st: Non-convergence in a ZIP model
Date   Tue, 11 Jan 2005 19:21:19 +0900

Arkadipta Ghosh wrote:

I am trying to run a Zero inflated Poisson model (both with and without fixed 
effects), and the ml estimation process does not converge even after hundreds 
of iterations. It keeps saying "not concave". I understand that in such cases 
one can write an ml program or try setting initial values to ensure a quicker 
convergence. I have tried both but something seems to be going wrong with 
those. In other words, I might be making some basic mistake somewhere or doing 
something wrong. Is there a better procedure or a good resource that I can look 
up (on the web, may be)? Sorry for this basic question but I am relatively new 
to ML estimation and thought you could help. Thanks,


By "both with and without fixed effect," do you mean that it won't converge 
even with a constant-only model, i.e., -zip response_variable, inflate(_cons)-? 
Or does it mean that you stll keep a lot of variables in the equation predictng 
zero counts, i.e., in the -inflate()- option?  If it's the latter, then some of 
the variables might be collinear or nearly collinear, or one or more might have 
a coefficient with maximum likelihood when it's essentially at infinity, or 
there might be a problem with scaling between the variables causing numerical 
problems.  (I don't have any particular insight into ZIP modeling, and these 
possibilities are just generalization of those given in a FAQ at StataCorp's 
website as to what might cause not-concave messages at at least the last 
iteration for -ml-, in general.  See 
and, in particular, the passages at the end of the section titled, Problem 2: 
Nonconcave log-likelihoods.)

Joseph Coveney

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