NAG Library Manual, Mark 28.7
```/* nag_correg_linregs_const (g02cac) Example Program.
*
* Copyright 2022 Numerical Algorithms Group.
*
* Mark 28.7, 2022.
*/

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

int main(void) {
Integer exit_status = 0, i, n;
Nag_SumSquare mean;
Nag_Boolean weight;
char nag_enum_arg[40];
double a, b, df, err_a, err_b, rsq, rss;
double *wt = 0, *wtptr, *x = 0, *y = 0;
NagError fail;

INIT_FAIL(fail);

printf("nag_correg_linregs_const (g02cac) Example Program Results\n");
/* Skip heading in data file */
scanf("%*[^\n]");
scanf(" %39s", nag_enum_arg);
/* nag_enum_name_to_value (x04nac).
* Converts NAG enum member name to value
*/
mean = (Nag_SumSquare)nag_enum_name_to_value(nag_enum_arg);
scanf(" %39s", nag_enum_arg);
weight = (Nag_Boolean)nag_enum_name_to_value(nag_enum_arg);
scanf("%" NAG_IFMT "", &n);
if (n >= (mean == Nag_AboutMean ? 2 : 1)) {
if (!(x = NAG_ALLOC(n, double)) || !(y = NAG_ALLOC(n, double)) ||
!(wt = NAG_ALLOC(n, double))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
} else {
printf("Invalid n.\n");
exit_status = 1;
return exit_status;
}

if (weight) {
wtptr = wt;
for (i = 0; i < n; ++i)
scanf("%lf%lf%lf", &x[i], &y[i], &wt[i]);
} else {
wtptr = (double *)0;
for (i = 0; i < n; ++i)
scanf("%lf%lf", &x[i], &y[i]);
}

/* nag_correg_linregs_const (g02cac).
* Simple linear regression with or without a constant term,
* data may be weighted
*/
nag_correg_linregs_const(mean, n, x, y, wtptr, &a, &b, &err_a, &err_b, &rsq,
if (fail.code != NE_NOERROR) {
printf("Error from nag_correg_linregs_const (g02cac).\n%s\n", fail.message);
exit_status = 1;
goto END;
}

printf("\nRegression constant a = %6.4f\n\n", a);
printf("Standard error of the regression constant a = %6.4f\n\n", err_a);
}

printf("Regression coefficient b = %6.4f\n\n", b);
printf("Standard error of the regression coefficient b = %6.4f\n\n", err_b);

printf("The regression coefficient of determination = %6.4f\n\n", rsq);
printf("The sum of squares of the residuals about the "
"regression = %6.4f\n\n",