[R] constrained optimization in R

[Spencer Graves]

      Have you considered doing an unconstrained penalized optimization, 
e.g.

       pen.f(x, X, penalty) = function(x)(f(x[1], x[2])+penalty*(g(x[1], 
x[2])-X)^2)

        Then give "pen.f" to optim.  Start out with "penalty" small, 
then use optim's answers with one value of penalty as starting values 
for optim with double or 10 times the penalty.  As long as f and g are 
reasonably well behaved, this should produce an answer without excessive 
effort. 

       hope this helps.  spencer graves      

Jason.L.Higbee at stls.frb.org wrote:

>R:
>
>I need to minimize a function such that the parameters when used in 
>another function result in a particular value, which i fix.  That is, I 
>need min(f(a,b)) given g(a,b)=X, where min(.) is the minimum, f(.) and 
>g(.) are functions (with unknown gradients) of parameters a and b and X is 
>a fixed value.  What optimization function(s) in R do you suggest? 
>constrOptim looks like it will work except I don't know the gradient of 
>the functions.
>
>Thanks,
>
>Jason Higbee
>
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-- 
Spencer Graves, PhD, Senior Development Engineer
O:  (408)938-4420;  mobile:  (408)655-4567