Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: gradient and the inverse of the information matrix


From   Maarten Buis <[email protected]>
To   [email protected]
Subject   Re: st: gradient and the inverse of the information matrix
Date   Thu, 2 May 2013 11:15:58 +0200

--- On Wed, May 1, 2013 at 11:40 PM, Jun Xu wrote:
>> I am working on a single-equation categorical dependent variable model. I estimated the model with constraints imposed. Then if I understand the score test correctly, it would be a simple matrix operation of
>>
>> gradient * inv(information matrix) * gradient'

--- On Thu, May 2, 2013 at 9:44 AM, Maarten Buis wrote:
> The gradient returned in e(gradient) is what it is supposed to be, but
> not what you want it to be. What e(gradient) gives you is the gradient
> of the constrained model at the estimated parameters of the
> constrained model. What you want is the gradient of the
> _unconstrained_ model at the parameter values of the constrained
> model.

The same is ofcourse true for e(V)

-- Maarten

---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
---------------------------------
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index