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st: RE: Re: Constraining OLS coefficients so that prediction satisfies a particular condition
From
Nick Cox <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: RE: Re: Constraining OLS coefficients so that prediction satisfies a particular condition
Date
Sat, 21 May 2011 13:07:00 +0100
Stata references
[R] ml . . . . . . . . . . . . . . . . . . Maximum likelihood estimation
(help ml, mleval, mlmethod)
Book . . . . . . . . Maximum Likelihood Estimation with Stata, 4th Edition
. . . . . . . . . William Gould, Jeffrey Pitblado, and William Sribney
http://www.stata.com/bookstore/ml4.html
FAQ . . . . . . . . . . . . . . . . . . . . Use of ml for nonlinear model
. . . . . . . . . . . . . . . . . . . . . . . . W. Guan and G. Sanchez
6/07 How to estimate a nonlinear model using ml?
http://www.stata.com/support/faqs/stat/nl_ml.html
Example . . . . . . . . . . . . . Capabilities: maximum likelihood estimation
http://www.stata.com/capabilities/mlexample.html
Example . . . . . Simple linear and nonlinear models using Stata's ml command
. . . . . . . . . . . . . . . . . . UCLA Academic Technology Services
6/09 http://www.ats.ucla.edu/stat/stata/code/simple_ml.htm
Nick
[email protected]
Amer Hasan
Thank you both.
Maarten do you have any sample code on using gmm to program ml?
Having never programmed my own ml, I am going to go over the archives
to see how others have gone about it. But I would also be grateful if
you could point me to a stata reference on how to program your own ml.
Thanks
Amer
On Fri, May 20, 2011 at 8:21 AM, Amer Hasan <[email protected]> wrote:
>
> Dear Statalist Users:
>
> I would like to perform the following calculation using Stata 10.1SE
> on a windows xp machine.
>
> reg y1 x1 x2 if year==1
>
> predict y2-hat if year==2, xb
>
> such that y1 - y2-hat = K
>
> y1 - is observed
>
> y2-hat - is the prediction using betas of year 1 and Xs of year 2.
>
> K is the observed difference between y1 and y2 (also observable).
>
> I know I can constrain the betas and that should change the
> prediction. What I am not sure about is how to do so in such a way
> that the prediction satisfies the condition. Any guidance on how to
> start would be much appreciated. I may also not be seeing the forest
> for the trees.
>
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