st: Maximizing under constraint with Mata ?

[Ozgur Ererdem <ozgur.ererdem@ecopa.com>]

Dear Stata users, 

I've been trying to implement an optimization under constraint, using the optimize() command of Mata. 
Both the function I'm willing to maximize and the constraint are non-linear. 

Below please find the code I am using to define the Lagrange function denoted as "Ref". p[K] is the Lagrange multiplier, and the other p[i]s are the unknown parameters I am looking for. I use a "d0" evaluatortype.

Mata have been unable to find a solution, because  it "cannot calculate numerical derivatives  -- discontinuous region with missing values encountered" 

Am I making a mistake in the way I write the problem? Has Mata the capacity to solve these kinds of optimization problems? Thank you very much for your help. 

Regards 



void mysolver(todo, p, Ref, S,H )
      {external alpha, w, M, txm, k, X 
	  delta = J(k, 1, 0) 
	  for (i=1; i<=k; i++) {
	  delta[i] = exp(X[i] + alpha*(p[i]*1.196))
	  } 	 
	  S0 = runningsum(delta) 
	
      CA = J(k, 1, 0) 
	  for (i=1; i<=k; i++) {
      CA[i] = p[i]*( (delta[i]/(1+S0[k]))*M )
	  }
	  CAtot = runningsum(CA)
	  
	  CT = J(k, 1, 0)
	  	  for (i=1; i<=k; i++) {
	  CT[i] = w[i]*( (delta[i]/(1+S0[k]))*M )
	  }
	  CTtot = runningsum(CT)
	  
	  K = k+1 
	  Ref = J(1,1,0) 
	  
	  Ref = CAtot[k] + p[K]*(((1-txm)*CAtot[k]) - CTtot[k]) 
	  
	 }




Özgür Kaan Ererdem
Economist 
ECOPA


Tél: +33 4 20 04 00 42 
Fax: +33 5 67 69 91 06
ozgur.ererdem@ecopa.com 
www.ecopa.com



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