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| 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 17:38:12 -0400 |
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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/