NAG Library Manual, Mark 28.5
```/* nag_correg_corrmat_target (g02apc) Example Program.
*
* Copyright 2022 Numerical Algorithms Group.
*
* Mark 28.5, 2022.
*/

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

int main(void) {

#define G(I, J) g[(J - 1) * pdg + I - 1]
#define H(I, J) h[(J - 1) * pdh + I - 1]

/*  Scalars */
Integer exit_status = 0;
Integer one = 1;
double alpha, eigmin, eigtol, errtol, norm, theta;
Integer i, j, iter, n, pdg, pdh, pdx;

/*  Arrays */
double *eig = 0, *g = 0, *h = 0, *x = 0;

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

INIT_FAIL(fail);

/* Output preamble */
printf("nag_correg_corrmat_target (g02apc)");
printf(" Example Program Results\n\n");
fflush(stdout);

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

/* Read in the problem size and theta */
scanf("%" NAG_IFMT "%lf%*[^\n] ", &n, &theta);

pdg = n;
pdh = n;
pdx = n;
if (!(eig = NAG_ALLOC(n, double)) || !(g = NAG_ALLOC(pdg * n, double)) ||
!(h = NAG_ALLOC(pdh * n, double)) || !(x = NAG_ALLOC(pdx * 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 matrix h */
for (i = 1; i <= n; i++)
for (j = 1; j <= n; j++)
scanf("%lf", &H(i, j));
scanf("%*[^\n] ");

/* Use the defaults for ERRTOL and EIGTOL */
errtol = -1.0;
eigtol = -1.0;

/*
* nag_correg_corrmat_target (g02apc).
* Calculate nearest correlation matrix using target matrix
*/
nag_correg_corrmat_target(g, pdg, n, theta, h, pdh, errtol, eigtol, x, pdx,
&alpha, &iter, &eigmin, &norm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_correg_corrmat_target (g02apc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}

/* Display results */

order = Nag_ColMajor;
/*
* nag_file_print_matrix_real_gen (x04cac).
* Prints real general matrix
*/
nag_file_print_matrix_real_gen(order, Nag_GeneralMatrix, Nag_NonUnitDiag, n,
n, g, pdg, "Symmetrised Input Matrix G", NULL,
&fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_real_gen (x04cac).\n%s\n",
fail.message);
exit_status = 2;
goto END;
}

printf("\n");
fflush(stdout);
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("Error from nag_file_print_matrix_real_gen (x04cac).\n%s\n",
fail.message);
exit_status = 3;
goto END;
}

printf("\n%s %9" NAG_IFMT " \n\n", "Number of iterations taken:", iter);
printf("%s %34.4f \n\n", "alpha: ", alpha);
printf("%s %29.4f \n\n", "norm value: ", norm);
printf("%s %34.4f \n\n", "theta: ", theta);
printf("%s %15.4f \n", "Smallest eigenvalue of A: ", eigmin);

/*
* 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("Error from nag_lapackeig_dsyev (f08fac).\n%s\n", fail.message);
exit_status = 4;
goto END;
}

printf("\n");
fflush(stdout);
/*
* 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, one,
n, eig, one, "Eigenvalues of x", NULL, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_real_gen (x04cac).\n%s\n",
fail.message);
exit_status = 5;
goto END;
}

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