NAG Library Manual, Mark 29.2
```/* nag_univar_ci_poisson (g07abc) Example Program.
*
* Copyright 2023 Numerical Algorithms Group.
*
* Mark 29.2, 2023.
*/

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

int main(void) {

/* Scalars */
double clevel, sum, tl, tu, xmean;
Integer exit_status, i, ifreq, n, num;
NagError fail;

INIT_FAIL(fail);

exit_status = 0;
printf("nag_univar_ci_poisson (g07abc) Example Program Results\n");

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

/* Read in the number of Noxious Seeds in a sub sample and
* the frequency with which that number occurs.
*/

/* Compute the sample mean */
sum = 0.0;
n = 0;
while (scanf("%" NAG_IFMT "%" NAG_IFMT "%*[^\n] ", &num, &ifreq) != EOF)
{
sum += (double)num * (double)ifreq;
n += ifreq;
}
xmean = sum / (double)n;

printf("\n");
printf("The point estimate of the Poisson parameter = %6.4f\n", xmean);
for (i = 1; i <= 2; ++i) {
if (i == 1) {
clevel = 0.95;
printf("\n");
printf("95 percent Confidence Interval for the estimate\n");
} else {
clevel = 0.99;
printf("99 percent Confidence Interval for the estimate\n");
}
/* nag_univar_ci_poisson (g07abc).
* Computes confidence interval for the parameter of a
* Poisson distribution
*/
nag_univar_ci_poisson(n, xmean, clevel, &tl, &tu, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_univar_ci_poisson (g07abc).\n%s\n", fail.message);
exit_status = 1;
goto END;
}

printf("( %6.4f , %6.4f )\n", tl, tu);
printf("\n");
}

END:
return exit_status;
}
```