```/* nag_regsn_mult_linear_add_var (g02dec) Example Program.
*
* NAGPRODCODE Version.
*
* Copyright 2016 Numerical Algorithms Group.
*
* Mark 26, 2016.
*/

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

#define X(I, J) x[(I) *tdx + J]
#define Q(I, J) q[(I) *tdq + J]

int main(void)
{
Integer exit_status = 0, i, indx, ip, ipmax, j, m, n, rank, tdq, tdx;
char nag_enum_arg[40];
double *b = 0, *cov = 0, *p = 0, *q = 0, *se = 0, *wt = 0, *wtptr;
double *x = 0, *xe = 0;
Nag_Boolean svd, weight;
Nag_IncludeMean mean;
NagError fail;

INIT_FAIL(fail);

/* 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);
ipmax = 5;
if (n >= 1 && m >= 1) {
if (!(wt = NAG_ALLOC(n, double)) ||
!(x = NAG_ALLOC((n) * (m), double)) ||
!(xe = NAG_ALLOC(n, double)) ||
!(b = NAG_ALLOC(ipmax, double)) ||
!(cov = NAG_ALLOC(ipmax * (ipmax + 1) / 2, double)) ||
!(p = NAG_ALLOC(ipmax * (ipmax + 2), double)) ||
!(se = NAG_ALLOC(ipmax, double)) ||
!(q = NAG_ALLOC((n) * (ipmax + 1), double))
)
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
tdx = m;
tdq = ipmax + 1;
}
else {
printf("Invalid n or m.\n");
exit_status = 1;
return exit_status;
}

if (weight)
wtptr = wt;
else
wtptr = (double *) 0;

if (wtptr) {
for (i = 0; i < n; i++) {
for (j = 0; j < m; j++)
scanf("%lf", &X(i, j));
scanf("%lf%lf", &Q(i, 0), &wt[i]);
}
}
else {
for (i = 0; i < n; i++) {
for (j = 0; j < m; j++)
scanf("%lf", &X(i, j));
scanf("%lf", &Q(i, 0));
}
}
/* Set tolerance */
tol = 0.000001e0;
ip = 0;
if (mean == Nag_MeanInclude) {
for (i = 0; i < n; ++i)
xe[i] = 1.0;

* Add a new independent variable to a general linear
* regression model
*/
tol, &fail);
if (fail.code != NE_NOERROR) {
fail.message);
exit_status = 1;
goto END;
}

ip = 1;
}
while (scanf("%" NAG_IFMT "", &indx) != EOF)
{
if (indx > 0) {
for (i = 0; i < n; i++)
xe[i] = X(i, indx - 1);
/* nag_regsn_mult_linear_add_var (g02dec), see above. */
tol, &fail);
if (fail.code == NE_NOERROR) {
ip += 1;
printf("Variable %4" NAG_IFMT " added\n", indx);

/* nag_regsn_mult_linear_upd_model (g02ddc).
* Estimates of regression parameters from an updated model
*/
nag_regsn_mult_linear_upd_model(n, ip, q, tdq, &rsst, &df, b, se,
cov, &svd, &rank, p, tol, &fail);
if (fail.code != NE_NOERROR) {
"\n%s\n", fail.message);
exit_status = 1;
goto END;
}

if (svd)
printf("Model not of full rank\n\n");
printf("Residual sum of squares = %13.4e\n", rsst);
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");
}
else if (fail.code == NE_NVAR_NOT_IND)
printf(" * New variable not added *\n");
else {
printf("Error from nag_regsn_mult_linear_upd_model (g02ddc)."
"\n%s\n", fail.message);
exit_status = 1;
goto END;
}
}
}

END:
NAG_FREE(wt);
NAG_FREE(x);
NAG_FREE(xe);
NAG_FREE(b);
NAG_FREE(cov);
NAG_FREE(p);
NAG_FREE(se);
NAG_FREE(q);

return exit_status;
}
```