```/* nag_tsa_uni_arima_resid (g13asc) Example Program.
*
* Copyright 2019 Numerical Algorithms Group.
*
* Mark 27.0, 2019.
*/

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

int main(void)
{
Integer exit_status = 0, i, idf, j, m, *mr = 0, narma, ni, npar;
Integer nres, nseries, nx;
NagError fail;
Nag_ArimaOrder arimav;
Nag_G13_Opt options;
Nag_TransfOrder transfv;
double chi, df, objf, *par = 0, *r = 0, *rc = 0, *res, s, *sd = 0,
siglev, *x = 0;

INIT_FAIL(fail);

printf("nag_tsa_uni_arima_resid (g13asc) Example Program Results\n\n");

/* Skip heading in data file */
scanf("%*[^\n]");
scanf("%" NAG_IFMT "%*[^\n]", &nx);
if (!(x = NAG_ALLOC(nx, double))
|| !(mr = NAG_ALLOC(7, Integer)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}

for (i = 1; i <= nx; ++i)
scanf("%lf", &x[i - 1]);
scanf("%*[^\n]");
for (i = 1; i <= 7; ++i)
scanf("%" NAG_IFMT "", &mr[i - 1]);
scanf("%*[^\n]");

npar = mr[0] + mr[2] + mr[3] + mr[5] + 1;
if (!(par = NAG_ALLOC(npar, double))
|| !(sd = NAG_ALLOC(npar, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
for (i = 1; i <= npar; ++i)
par[i - 1] = 0.0;

nseries = 1;
arimav.p = mr[0];
arimav.d = mr[1];
arimav.q = mr[2];
arimav.bigp = mr[3];
arimav.bigd = mr[4];
arimav.bigq = mr[5];
arimav.s = mr[6];
/* nag_tsa_options_init (g13bxc).
* Initialization function for option setting
*/
nag_tsa_options_init(&options);
/* nag_tsa_transf_orders (g13byc).
* Allocates memory to transfer function model orders
*/
nag_tsa_transf_orders(nseries, &transfv, &fail);
/* nag_tsa_multi_inputmod_estim (g13bec).
* Estimation for time series models
*/
fflush(stdout);
nag_tsa_multi_inputmod_estim(&arimav, nseries, &transfv, par, npar, nx, x,
nseries, sd, &s, &objf, &df, &options, &fail);
nres = options.lenres;
res = options.res;
if (fail.code != NE_NOERROR) {
printf("Error from nag_tsa_multi_inputmod_estim (g13bec).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}

m = 10;
if (!(r = NAG_ALLOC(m, double))
|| !(rc = NAG_ALLOC(m * m, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}

narma = mr[0] + mr[2] + mr[3] + mr[5];
/* nag_tsa_uni_arima_resid (g13asc).
* Univariate time series, diagnostic checking of residuals,
* following nag_tsa_multi_inputmod_estim (g13bec)
*/
nag_tsa_uni_arima_resid(&arimav, nres, res, m, par, narma, r, rc,
m, &chi, &idf, &siglev, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_tsa_uni_arima_resid (g13asc).\n%s\n", fail.message);
exit_status = 1;
goto END;
}
printf("\nRESIDUAL AUTOCORRELATION FUNCTION");
printf("\n---------------------------------\n\n");
for (j = 0; j <= (m - 1) / 7; j++) {
ni = MIN(7, m - j * 7);
printf("LAG  K  ");
for (i = 0; i < ni; i++)
printf("%5" NAG_IFMT "  ", i + j * 7 + 1);
printf("\nR(K)    ");
for (i = 0; i < ni; i++)
printf("%7.3f", r[i + j * 7]);
printf("\nST.ERROR");
for (i = 0; i < ni; i++)
printf("%7.3f", rc[(m + 1) * (i + j * 7)]);
printf("\n---------------------------------------------------------\n");
}
/* nag_tsa_free (g13xzc).
* Freeing function for use with g13 option setting
*/
nag_tsa_free(&options);

END:
NAG_FREE(x);
NAG_FREE(mr);
NAG_FREE(par);
NAG_FREE(sd);
NAG_FREE(r);
NAG_FREE(rc);
return exit_status;
}
```