st: question RE -ml- and ancillary parameters

[Phil Schumm <pschumm@uchicago.edu>]

Hi,

I am coding an estimator for a model in which the number of ancillary  
parameters depends on the observed support of the dependent variable  
-- very similar to an ordinal probit or logit model.  My first step  
was to translate R code I was given which successfully estimates the  
model into Stata (mostly into Mata); now, I would like to re- 
implement the estimator using -ml- to explore the performance  
differences and to access all of the -ml- related goodness (e.g.,  
hooks for robust estimates of variance, svy capability, and  
constrained estimation).

I have used -ml- frequently in the past, but never with a problem  
like this.  Unfortunately, -_oprobit- and -_ologit- (the underlying  
commands which implement -oprobit- and -ologit-) are built-in, so I  
can't see how they handle this issue.  My first instinct would be to  
construct an -ml model- statement programmatically based on the data  
and then execute it.  Is this a reasonable approach, and are there  
any practical limits to the number of ancillary parameters (i.e.,  
equations) that can be specified this way?

Thanks,


-- Phil

*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/