NAG Library Manual, Mark 28.7
```/* nag_correg_corrmat_nearest_bounded (g02abc) Example Program.
*
* Copyright 2022 Numerical Algorithms Group.
*
* Mark 28.7, 2022.
*/

#include <nag.h>

int main(void) {

/* Scalars */
Integer exit_status = 0;
double alpha, errtol, nrmgrd;
Integer feval, i, iter, j, maxit, maxits, n, pdeig, pdg, pdx;

/* Arrays */
char nag_enum_arg[100];
double *eig = 0, *g = 0, *w = 0, *x = 0;

/* Nag Types */
Nag_OrderType order;
Nag_NearCorr_ProbType opt;
NagError fail;

INIT_FAIL(fail);

#ifdef NAG_COLUMN_MAJOR
#define G(I, J) g[(J - 1) * pdg + I - 1]
order = Nag_ColMajor;
#else
#define G(I, J) g[(I - 1) * pdg + J - 1]
order = Nag_RowMajor;
#endif

/* Output preamble */
printf("nag_correg_corrmat_nearest_bounded (g02abc)");
printf(" Example Program Results\n\n");
fflush(stdout);

/* Skip heading in data file */
scanf("%*[^\n] ");
/* Read in the problem size, opt and alpha */
scanf("%" NAG_IFMT "", &n);
scanf("%39s", nag_enum_arg);
/*
* nag_enum_name_to_value (x04nac).
* Converts NAG enum member name to value
*/
opt = (Nag_NearCorr_ProbType)nag_enum_name_to_value(nag_enum_arg);
scanf("%lf%*[^\n]", &alpha);

pdg = n;
pdx = n;
if (order == Nag_ColMajor)
pdeig = 1;
else
pdeig = n;

if (!(g = NAG_ALLOC((pdg) * (n), double)) || !(w = NAG_ALLOC((n), double)) ||
!(x = NAG_ALLOC((pdx) * (n), double)) ||
!(eig = NAG_ALLOC((n), double))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}

/* Read in the matrix g */
for (i = 1; i <= n; i++)
for (j = 1; j <= n; j++)
scanf("%lf", &G(i, j));
scanf("%*[^\n] ");

/* Read in the vector w */
for (i = 0; i < n; i++)
scanf("%lf", &w[i]);
scanf("%*[^\n] ");

/* Use the defaults for errtol, maxits and maxit */
errtol = 0.0;
maxits = 0;
maxit = 0;

/*
* nag_correg_corrmat_nearest_bounded (g02abc).
* Computes the nearest correlation matrix incorporating weights
* and/or bounds
*/
nag_correg_corrmat_nearest_bounded(order, g, pdg, n, opt, alpha, w, errtol,
maxits, maxit, x, pdx, &iter, &feval,
&nrmgrd, &fail);
if (fail.code != NE_NOERROR) {
printf("%s\n", fail.message);
exit_status = 1;
goto END;
}

/*
* nag_file_print_matrix_real_gen (x04cac).
* Print real general matrix (easy-to-use)
*/
nag_file_print_matrix_real_gen(order, Nag_GeneralMatrix, Nag_NonUnitDiag, n,
n, x, pdx, "Nearest Correlation Matrix x",
NULL, &fail);
if (fail.code != NE_NOERROR) {
printf("%s\n", fail.message);
exit_status = 1;
goto END;
}
printf("\nNumber of Newton steps taken: %11" NAG_IFMT "\n", iter);
printf("Number of function evaluations: %9" NAG_IFMT "\n\n", feval);
printf("alpha: %37.3f \n\n", alpha);
fflush(stdout);

/* nag_lapackeig_dsyev (f08fac).
* Computes all eigenvalues and, optionally, eigenvectors of a real
* symmetric matrix
*/
nag_lapackeig_dsyev(order, Nag_EigVals, Nag_Upper, n, x, pdx, eig, &fail);
if (fail.code != NE_NOERROR) {
printf("%s\n", fail.message);
exit_status = 1;
goto END;
}

/* nag_file_print_matrix_real_gen (x04cac).
* Print real general matrix (easy-to-use)
*/
nag_file_print_matrix_real_gen(order, Nag_GeneralMatrix, Nag_NonUnitDiag, 1,
n, eig, pdeig, "Eigenvalues of x", NULL,
&fail);
if (fail.code != NE_NOERROR) {
printf("%s\n", fail.message);
exit_status = 1;
}

END:
NAG_FREE(eig);
NAG_FREE(g);
NAG_FREE(w);
NAG_FREE(x);
return exit_status;
}
```