/* unconditional mutual information, to be used for the asymptotic test. */
SEXP mi(SEXP x, SEXP y, SEXP gsquare) {
int llx = NLEVELS(x), lly = NLEVELS(y), num = LENGTH(x);
int *xx = INTEGER(x), *yy = INTEGER(y);
double *res = NULL;
SEXP result;
PROTECT(result = allocVector(REALSXP, 2));
res = REAL(result);
res[0] = c_mi(xx, &llx, yy, &lly, &num);
res[1] = (double)(llx - 1) * (double)(lly - 1);
/* rescale to match the G^2 test. */
if (isTRUE(gsquare))
res[0] *= 2 * num;
UNPROTECT(1);
return result;
}/*MI*/
/* compute all the pairwise mutual information coefficients between the variables. */
void mi_matrix(double *mim, void **columns, int dim, int *nlevels, int *num,
void *cond, int *clevels, int *est) {
int i = 0, j = 0;
switch(*est) {
case DISCRETE_MAXIMUM_LIKELIHOOD:
if (cond == NULL) {
for (i = 0; i < dim; i++) {
for (j = i + 1; j < dim; j++) {
mim[UPTRI3(i + 1, j + 1, dim)] =
c_mi(((int **)columns)[i], nlevels + i,
((int **)columns)[j], nlevels + j, num);
}/*FOR*/
}/*FOR*/
}/*THEN*/
else {
for (i = 0; i < dim; i++) {
for (j = i + 1; j < dim; j++) {
mim[UPTRI3(i + 1, j + 1, dim)] =
c_cmi(((int **)columns)[i], nlevels + i,
((int **)columns)[j], nlevels + j,
(int *)cond, clevels, num);
}/*FOR*/
}/*FOR*/
}/*ELSE*/
break;
case GAUSSIAN_MAXIMUM_LIKELIHOOD:
for (i = 0; i < dim; i++) {
for (j = i + 1; j < dim; j++) {
mim[UPTRI3(i + 1, j + 1, dim)] =
c_mig(((double **)columns)[i], ((double **)columns)[j], num);
}/*FOR*/
}/*FOR*/
break;
}/*SWITCH*/
}/*MI_MATRIX*/
