I've searched to find examples of how to work with the C versions of
optim.
I've separated out the function just to test on it alone, and currently I'm
attempting to use fmmin as follows:
!~~CODE ~~!
double optimfn(int n, double *par, void *ex) {
double * lambda = (double*)malloc(sizeof(double)*n);
double sum = 0;
for(int i =0; i < n; i++) { lambda[i] = (1+tanh(par[i]/2.0))/2.0; }
for(int i = 0; i < n; i++) { sum += (par[i]*log(lambda[i]) +
(1-par[i]*log(1-lambda[i]))); }
return sum;
}
void optimgr(int n, double *par, double *gr, void *ex)
{
for(int i = 0; i < n; i++) { gr[i] = log(par[i]) - log(1-par[i]); }
}
void Test(SEXP SomeValues)
{
PROTECT(SomeValues = AS_NUMERIC(SomeValues));
double * CValues = NUMERIC_POINTER(SomeValues);
void * optEx, *grEx, *overallEx;
int mask = -1, fncount, grcount, failed;
double *Fmax, *gradients;
int size = sizeof(CValues)/sizeof(double);
vmmin(size, CValues, Fmax,
optimfn,
optimgr,
20, 0, mask, .00001, .000001, 40,
overallEx, fncount, grcount, failed);
}
!~~ END CODE ~~!
----------------------------------------------
Beyond the basic optimfn/optimgr which I'll be changing...
I've gotten compiler complaints about the 'implicit declaration of vmmin',
which I'm a little stuck on. But even beyond that, I'm unclear as to how
all of the information will be returned. The "R Extensions" does a lot of
hand-waving on this subject.
Could anyone provide a solid example of how this would be done properly?
Also, with an output of things like the loglikelihood and gradient values,
as I need to work with the returned values and not simply pass things
straight back into R.
I hope that was phrased clearly and not asking too much. I've looked
through the manuals and other mail list questions I could find, but feel
very stuck still.
Thanks in advance,
~Eddie
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