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st: constrained linear least-squares problems without using ML


From   "ali hashemi" <hashemi@vt.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: constrained linear least-squares problems without using ML
Date   Tue, 28 Jun 2011 21:51:37 -0400

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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