```/* nag_simple_linear_regression (g02cac) Example Program.
*
* Copyright 2014 Numerical Algorithms Group.
*
* Mark 3, 1992.
* Mark 8 revised, 2004.
*/

#include <nag.h>
#include <stdio.h>
#include <nag_stdlib.h>
#include <nagg02.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_simple_linear_regression (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("%ld", &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_simple_linear_regression (g02cac).
* Simple linear regression with or without a constant term,
* data may be weighted
*/
nag_simple_linear_regression(mean, n, x, y, wtptr, &a, &b, &err_a, &err_b,
if (fail.code != NE_NOERROR)
{
printf("Error from nag_simple_linear_regression (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 "