RE: st: Optimize

[Mohamud Hussein <Mohamud.Hussein@fera.gsi.gov.uk>]

Thanks Austin.

I used code below as suggested but had no luck yet. I am sure it has something to do with my complete lack of knowledge in mata language.

I attach my data. I would be grateful if you can check for me where I am getting it wrong.

Many thanks,
Mohamud

==

void q(todo,x,y,g,H)
{
 crit=(3x^2+2x+1)^2
}
sol=J(1,0,0)
void grid(n1,n2)
{
 external sol, p
 for (i=n1; i<=n2; i++) {
  init=i
 S=optimize_init()
 optimize_init_evaluator(S, &q())
 optimize_init_which(S,"min")
 optimize_init_evaluatortype(S,"d0")
 optimize_init_params(S,init)
 p=round(optimize(S),10e-4)
 if (!anyof(sol, p)) {
  sol=(sol,p)
  }
 }
 sol
}
grid(-10,10)

==


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Austin Nichols
Sent: 23 July 2012 15:26
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Optimize

Mohamud Hussein <Mohamud.Hussein@fera.gsi.gov.uk>:
Looks like you are trying to maximize the unbounded quadratic rather
than find its zeros.  Use a root finder instead e.g.
http://www.stata.com/statalist/archive/2007-12/msg00551.html
http://www.stata.com/statalist/archive/2009-01/msg01140.html
but note first that the particular example you gave has no zeros (so
no interior solution).

On Sun, Jul 22, 2012 at 9:59 AM, Mohamud Hussein
<Mohamud.Hussein@fera.gsi.gov.uk> wrote:
> Hi there,
>
> I am trying to run a model for a marginal cost curve equation based on the traditional cubic total cost curve function (i.e. y= x^3+X^2+X+c) using Stata's optimize() command. The goal is to estimate the value of x which minimises y subject to a number of constraints.
>
> When I tried to specify the marginal cost curve function in mata directly as y=3x^2+2x+1 (i.e. first derivative of the total cost equation) I got the following message:
>
> Iteration 0:   f(p) =          1  (not concave)
> Iteration 1:   f(p) =  7.911e+71  (not concave)
> Iteration 2:   f(p) =  1.95e+169  (not concave)
> Iteration 3:   f(p) =  8.32e+250  (not concave)
> Iteration 4:   f(p) =  1.62e+288  (not concave)
> Iteration 5:   f(p) =  2.34e+306
> Hessian is not negative semidefinite
>
> I have never used Stata's mata programming language before and am not quite sure of what do here? Grateful if someone can help me on this.
>
> Thanks,
> Mohamud

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Attachment: FD data_SL sample.dta
Description: FD data_SL sample.dta