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Re: st: Using nonlinear constraints in an ordered probit

From   Maarten buis <[email protected]>
To   [email protected]
Subject   Re: st: Using nonlinear constraints in an ordered probit
Date   Wed, 20 Jan 2010 08:36:20 +0000 (GMT)

--- On Tue, 19/1/10, Dana Chandler wrote:
> oprobit y pop_1 pop_2 pop_3 pop_4
> ... and I would like to constrain each successive
> population parameter has a coefficient lower than the
> previous so that (pop_2-pop_1)>=0, (pop_3-pop_2)>=0, etc.
> I recognize that there has been a thread (and faq) from a
> few years back (<
intconst.html>) explaining how to set up interval (non-linear)
> constraints using ML to perform a linear regression. However,
> even though the article suggests that I could use the similar 
> methodology to derive it for probits, I'm not 100% sure that
> it's directly applicable in my case and for oprobits. 

It is also applicable to oprobit, or any other model.

> I have not worked with stata's ML function before. Does
> anyone have any advice? 

If you are serious about getting into this type of modeling then
you can't go wrong by getting: William Gould, Jeffrey Pitblado, 
William Sribney (2006) Maximum Likelihood Estimation with Stata. 
College Station: Stata Press.

Hope this helps,

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen


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