st: Using multiple equations with Optimize()

["Andrew Lynch" <aalhc5@mizzou.edu>]

Stata Users,

I have run into a bit of a dilemma with programing a Kalman filter with the 
optimize() procedure.  I have the full documentation and have not been able 
to clarify where exactly the optimize() command looks when it optimizes.  I 
am minimizing the process below.  My goal is to minimize the Log Likelihood 
function, but while I have observed data yt and xt, a and at are unobserved 
and my goal is to generate them.  To do so, I need Stata to rerun the do 
loop every time it updates one of the four parameters (b1, b2, q and h).  I 
say all that to ask the question, "Does optimize() only look to the v= 
equation to optimize with the parameters or does it look to the entire 
evaluation and move through it in some ordered fashion (thereby honoring the 
do loop)?"  I have been unable to get this to run, and I am unsure whether 
it is my dumb coding error at some point or just that optimize() won't do 
what I want it to do.

Any enlightenment would be greatly appreciated!

Thanks,

Andrew Lynch
PhD Student
Department of Finance
Trulaske School of Busineses
University of Missouri - Columbia

/* Optimization Procedure */

void maxlik(todo, b, xt, yt, v, g, h)
{
     b1=b[1]
     b2=b[2]
     q=b[3]
     h=b[4]
     i=1

     do {
          a[i]=b1*at[i] + b2*xt[i]
          p[i]=(b1)^2*pt[i] + q
          y[i]=a[i]
          f[i]=ft[i] + h
          at[i+1]=a[i] + ft[i+1]*p[i]*(yt[i]-y[i])
          pt[i+1]=p[i] - ft[i+1]*p[i]*p[i]
          L[i]=(.5)/f[i] + (.5)*(yt[i]-y[i])*(yt[i]-y[i])/f[i]
          i=i+1

     } while(i<(n+1))

 v=sum(L)
}

S = optimize_init()
optimize_init_evaluator(S, &maxlik())
optimize_init_evaluatortype(S, "d0")
optimize_init_params(S, (0,0,0,0))
optimize_init_which(S, "min")
optimize_init_argument(S, 1, xt)
optimize_init_argument(S, 2, yt)
b=optimize(S) 
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