NAG Library Manual, Mark 29
```/* nag_correg_corrmat (g02bxc) Example Program.
*
* Copyright 2023 Numerical Algorithms Group.
*
* Mark 29.0, 2023.
*/

#include <nag.h>
#include <stdio.h>

#define X(I, J) x[(I)*tdx + J]
#define R(I, J) r[(I)*tdr + J]
#define V(I, J) v[(I)*tdv + J]
int main(void) {
Integer exit_status = 0, i, j, m, n, tdr, tdv, tdx, test;
NagError fail;
char w;
double *r = 0, *std = 0, sw, *v = 0, *wmean = 0, *wt = 0, *wtptr, *x = 0;

INIT_FAIL(fail);

printf("nag_correg_corrmat (g02bxc) Example Program Results\n");

/* Skip heading in data file */
scanf("%*[^\n]");

test = 0;
while ((scanf("%" NAG_IFMT "%" NAG_IFMT " %c", &m, &n, &w) != EOF))
{
if (m >= 1 && n >= 1) {
if (!(x = NAG_ALLOC(n * m, double)) || !(r = NAG_ALLOC(m * m, double)) ||
!(v = NAG_ALLOC(m * m, double)) || !(wt = NAG_ALLOC(n, double)) ||
!(wmean = NAG_ALLOC(m, double)) || !(std = NAG_ALLOC(m, double))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
tdx = m;
tdr = m;
tdv = m;
} else {
printf("Invalid m or n.\n");
exit_status = 1;
return exit_status;
}
for (i = 0; i < n; i++)
scanf("%lf", &wt[i]);
for (i = 0; i < n; i++)
for (j = 0; j < m; j++)
scanf("%lf", &X(i, j));

if (w == 'w')
wtptr = wt;
else
wtptr = (double *)0;

/* nag_correg_corrmat (g02bxc).
* Product-moment correlation, unweighted/weighted
* correlation and covariance matrix, allows variables to be
* disregarded
*/
nag_correg_corrmat(n, m, x, tdx, (Integer *)0, wtptr, &sw, wmean, std, r,
tdr, v, tdv, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_correg_corrmat (g02bxc).\n%s\n", fail.message);
exit_status = 1;
goto END;
}

if (wtptr)
printf("\nCase %" NAG_IFMT " --- Using weights\n", ++test);
else
printf("\nCase %" NAG_IFMT " --- Not using weights\n", ++test);

printf("\nInput data\n");
for (i = 0; i < n; i++)
printf("%6.1f%6.1f%6.1f%6.1f\n", X(i, 0), X(i, 1), X(i, 2), wt[i]);

printf("\n");
printf("Sample means.\n");
for (i = 0; i < m; i++)
printf("%6.1f\n", wmean[i]);
printf("\nStandard deviation.\n");
for (i = 0; i < m; i++)
printf("%6.1f\n", std[i]);

printf("\nCorrelation matrix.\n");
for (i = 0; i < m; i++) {
for (j = 0; j < m; j++)
printf("  %7.4f  ", R(i, j));
printf("\n");
}

printf("\nVariance matrix.\n");
for (i = 0; i < m; i++) {
for (j = 0; j < m; j++)
printf("  %7.3f  ", V(i, j));
printf("\n");
}
printf("\nSum of weights %6.1f\n", sw);
END:
NAG_FREE(x);
NAG_FREE(r);
NAG_FREE(v);
NAG_FREE(wt);
NAG_FREE(wmean);
NAG_FREE(std);
}
return exit_status;
}
```