/* nag_correg_lars (g02mac) Example Program.
*
* Copyright 2024 Numerical Algorithms Group.
*
* Mark 30.0, 2024.
*/
/* Pre-processor includes */
#include <nag.h>
#include <stdio.h>
int main(void) {
/* Integer scalar and array declarations */
Integer i, j, k, ip, ldb, ldd, m, mnstep, n, nstep, lropt;
Integer *isx = 0;
Integer exit_status = 0;
/* NAG structures and types */
NagError fail;
Nag_LARSModelType mtype;
Nag_LARSPreProcess pred, prey;
/* Double scalar and array declarations */
double *b = 0, *d = 0, *fitsum = 0, *y = 0, *ropt = 0;
/* Character scalar and array declarations */
char cmtype[40], cpred[40], cprey[40];
/* Initialize the error structure */
INIT_FAIL(fail);
printf("nag_correg_lars (g02mac) Example Program Results\n\n");
/* Skip heading in data file */
scanf("%*[^\n] ");
/* Read in the problem size */
scanf("%" NAG_IFMT "%" NAG_IFMT "%*[^\n] ", &n, &m);
/* Read in the model specification */
scanf("%39s%39s%39s%" NAG_IFMT "%*[^\n] ", cmtype, cpred, cprey, &mnstep);
mtype = (Nag_LARSModelType)nag_enum_name_to_value(cmtype);
pred = (Nag_LARSPreProcess)nag_enum_name_to_value(cpred);
prey = (Nag_LARSPreProcess)nag_enum_name_to_value(cprey);
/* Using all variables */
isx = 0;
/* Optional arguments (using defaults) */
lropt = 0;
ropt = 0;
/* Allocate memory for the data */
ldd = n;
if (!(y = NAG_ALLOC(n, double)) || !(d = NAG_ALLOC(ldd * m, double))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
/* Read in the data */
for (i = 0; i < n; i++) {
for (j = 0; j < m; j++) {
scanf("%lf", &d[j * ldd + i]);
}
scanf("%lf", &y[i]);
}
scanf("%*[^\n] ");
/* Allocate output arrays */
ldb = m;
if (!(b = NAG_ALLOC(ldb * (mnstep + 2), double)) ||
!(fitsum = NAG_ALLOC(6 * (mnstep + 1), double))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
/* Call nag_correg_lars (g02mac) to fit the model */
nag_correg_lars(mtype, pred, prey, n, m, d, ldd, isx, y, mnstep, &ip, &nstep,
b, ldb, fitsum, ropt, lropt, &fail);
if (fail.code != NE_NOERROR) {
if (fail.code != NW_OVERFLOW_WARN && fail.code != NW_POTENTIAL_PROBLEM &&
fail.code != NW_LIMIT_REACHED) {
printf("Error from nag_correg_lars (g02mac).\n%s\n", fail.message);
exit_status = 11;
goto END;
} else {
printf("Warning from nag_correg_lars (g02mac).\n%s\n", fail.message);
exit_status = 2;
}
}
/* Display the parameter estimates */
printf(" Step ");
for (i = 0; i < MAX(ip - 2, 0) * 5; i++)
printf(" ");
printf(" Parameter Estimate\n ");
for (i = 0; i < 5 + ip * 10; i++)
printf("-");
printf("\n");
for (k = 0; k < nstep; k++) {
printf(" %3" NAG_IFMT "", k + 1);
for (j = 0; j < ip; j++) {
printf(" %9.3f", b[k * ldb + j]);
}
printf("\n");
}
printf("\n");
printf(" alpha: %9.3f\n", fitsum[6 * nstep]);
printf("\n");
printf(" Step Sum RSS df Cp Ck Step Size\n ");
for (i = 0; i < 64; i++)
printf("-");
printf("\n");
for (k = 0; k < nstep; k++) {
printf(" %3" NAG_IFMT " %9.3f %9.3f %6.0f %9.3f %9.3f %9.3f\n", k + 1,
fitsum[k * 6], fitsum[k * 6 + 1], fitsum[k * 6 + 2],
fitsum[k * 6 + 3], fitsum[k * 6 + 4], fitsum[k * 6 + 5]);
}
printf("\n");
printf(" sigma^2: %9.3f\n", fitsum[nstep * 6 + 4]);
END:
NAG_FREE(y);
NAG_FREE(d);
NAG_FREE(b);
NAG_FREE(fitsum);
NAG_FREE(ropt);
return (exit_status);
}