```/* nag_regsn_mult_linear_tran_model (g02dkc) Example Program.
*
* Copyright 2017 Numerical Algorithms Group.
*
* Mark 26.2, 2017.
*/

#include <nag.h>
#include <stdio.h>
#include <nag_stdlib.h>
#include <nagg02.h>

#define X(I, J) x[(I) *tdx + J]
#define C(I, J) c[(I) *tdc + J]
int main(void)
{
Integer exit_status = 0, i, iconst, ip, j, m, n, rank, *sx = 0, tdc,
tdq, tdx;
double df, rss, tol;
double *b = 0, *c = 0, *com_ar = 0, *cov = 0, *h = 0, *p = 0;
double *q = 0, *res = 0, *se = 0, *wt = 0, *wtptr, *x = 0, *y = 0;
char nag_enum_arg[40];
Nag_Boolean svd, weight;
Nag_IncludeMean mean;
NagError fail;

INIT_FAIL(fail);

printf("nag_regsn_mult_linear_tran_model (g02dkc) Example Program "
"Results\n");
/* Skip heading in data file */
scanf("%*[^\n]");
scanf("%" NAG_IFMT " %" NAG_IFMT "", &n, &m);
scanf(" %39s", nag_enum_arg);
/* nag_enum_name_to_value (x04nac).
* Converts NAG enum member name to value
*/
weight = (Nag_Boolean) nag_enum_name_to_value(nag_enum_arg);
scanf(" %39s", nag_enum_arg);
mean = (Nag_IncludeMean) nag_enum_name_to_value(nag_enum_arg);
if (n >= 2 && m >= 1) {
if (!(h = NAG_ALLOC(n, double)) ||
!(res = NAG_ALLOC(n, double)) ||
!(wt = NAG_ALLOC(n, double)) ||
!(x = NAG_ALLOC(n * m, double)) ||
!(y = NAG_ALLOC(n, double)) || !(sx = NAG_ALLOC(m, Integer)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
tdx = m;
}
else {
printf("Invalid n.\n");
exit_status = 1;
return exit_status;
}
if (weight) {
wtptr = wt;
for (i = 0; i < n; i++) {
for (j = 0; j < m; j++)
scanf("%lf", &X(i, j));
scanf("%lf%lf", &y[i], &wt[i]);
}
}
else {
wtptr = (double *) 0;
for (i = 0; i < n; i++) {
for (j = 0; j < m; j++)
scanf("%lf", &X(i, j));
scanf("%lf", &y[i]);
}
}
for (j = 0; j < m; j++)
scanf("%" NAG_IFMT "", &sx[j]);
scanf("%" NAG_IFMT "", &ip);

if (!(b = NAG_ALLOC(ip, double)) ||
!(c = NAG_ALLOC((ip) * (ip), double)) ||
!(cov = NAG_ALLOC(ip * (ip + 1) / 2, double)) ||
!(p = NAG_ALLOC(ip * (ip + 2), double)) ||
!(q = NAG_ALLOC(n * (ip + 1), double)) ||
!(se = NAG_ALLOC(ip, double)) ||
!(com_ar = NAG_ALLOC(ip * ip + ip, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
tdq = ip + 1;
tdc = ip;

/* Set tolerance */
tol = 0.00001e0;
/* Find initial estimates using nag_regsn_mult_linear (g02dac) */
/* nag_regsn_mult_linear (g02dac).
* Fits a general (multiple) linear regression model
*/
nag_regsn_mult_linear(mean, n, x, tdx, m, sx, ip, y, wtptr,
&rss, &df, b, se, cov, res, h, q, tdq,
&svd, &rank, p, tol, com_ar, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_regsn_mult_linear (g02dac).\n%s\n", fail.message);
exit_status = 1;
goto END;
}

printf("Estimates from g02dac\n\n");
printf("Residual sum of squares = %13.4e\n", rss);
printf("Degrees of freedom = %3.1f\n\n", df);
printf("Variable   Parameter estimate   Standard error\n\n");
for (j = 0; j < ip; j++)
printf("%6" NAG_IFMT "%20.4e%20.4e\n", j + 1, b[j], se[j]);
printf("\n");
/*
*    Input constraints and call nag_regsn_mult_linear_tran_model (g02dkc)
*/
iconst = ip - rank;
for (i = 0; i < ip; ++i)
for (j = 0; j < iconst; ++j)
scanf("%lf", &C(i, j));

/* nag_regsn_mult_linear_tran_model (g02dkc).
* Estimates of parameters of a general linear regression
* model for given constraints
*/
nag_regsn_mult_linear_tran_model(ip, iconst, p, c, tdc, b, rss, df, se, cov,
&fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_regsn_mult_linear_tran_model (g02dkc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}

printf("\n");
printf("Estimates from nag_regsn_mult_linear_tran_model (g02dkc) using "
"constraints\n\n");
printf("Variable    Parameter estimate   Standard error\n\n");
for (j = 0; j < ip; j++)
printf("%6" NAG_IFMT "%20.4e%20.4e\n", j + 1, b[j], se[j]);
printf("\n");

END:
NAG_FREE(h);
NAG_FREE(res);
NAG_FREE(wt);
NAG_FREE(x);
NAG_FREE(y);
NAG_FREE(sx);
NAG_FREE(b);
NAG_FREE(c);
NAG_FREE(cov);
NAG_FREE(p);
NAG_FREE(q);
NAG_FREE(se);
NAG_FREE(com_ar);

return exit_status;
}
```