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Re: st: constrained linear least-squares problems without using ML


From   Steven Samuels <sjsamuels@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: constrained linear least-squares problems without using ML
Date   Wed, 29 Jun 2011 17:50:51 -0400


Actually, the following message provides the solution:

http://www.stata.com/statalist/archive/2011-06/msg00128.html


Ali,

you need to use -nl-.  See the example at:

http://www.stata.com/statalist/archive/2011-06/msg00110.html 

Steve
sjsamuels@gmail.com


On Jun 28, 2011, at 9:51 PM, ali hashemi wrote:

Dear list members,

I would like to estimate an OLS model (y=b1*x1+b2*x2) with proportionate
coefficients which means considering the following constraints:
b1>0
b2>0
b1+b2=1

I tried to estimate this using ML (for more details: findit inequality
constraints)

It works for some cases. Unfortunately, for many other cases it keeps giving
this message: "flat or discontinuous region encountered"

I'm told that ML is not the best option to estimate constrained linear
least-squares models. lsqlin in MATLAB and quadratic programming in R are
solutions that I have found in other packages. However, I'm not aware of any
alternative method in Stata? Does anyone have any idea how constrained
linear least-squares models can be estimated without using ML? 

Your help is greatly appreciated.
Best,
Ali



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