/* nag_regsn_mult_linear_upd_model (g02ddc) Example Program.
 *
 * Copyright 2017 Numerical Algorithms Group.
 *
 * Mark 26.1, 2017.
 */

#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, ip, ipmax, j, m, n, rank, tdq, tdx;
  double *b = 0, *cov = 0, df, *p = 0, *q = 0, rss, *se = 0, tol, *wt = 0;
  double *wtptr, *x = 0, *xe = 0;
  char nag_enum_arg[40];
  Nag_Boolean svd, weight;
  NagError fail;

  INIT_FAIL(fail);

  printf("nag_regsn_mult_linear_upd_model (g02ddc) Example Program Results\n");
  /* Skip heading in data file */
  scanf("%*[^\n]");
  scanf("%" NAG_IFMT " %" NAG_IFMT " %39s", &n, &m, 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);
  ipmax = 4;
  if (n >= 1 && m >= 1) {
    if (!(b = NAG_ALLOC(ipmax, double)) ||
        !(cov = NAG_ALLOC(ipmax * (ipmax + 1) / 2, double)) ||
        !(p = NAG_ALLOC(ipmax * (ipmax + 2), double)) ||
        !(wt = NAG_ALLOC(n, double)) ||
        !(x = NAG_ALLOC(n * m, double)) ||
        !(xe = NAG_ALLOC(n, 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;
  for (j = 0; j < m; ++j) {
    /*
     *        Fit model using g02dec
     */
    for (i = 0; i < n; i++)
      xe[i] = X(i, j);
    /* nag_regsn_mult_linear_add_var (g02dec).
     * Add a new independent variable to a general linear
     * regression model
     */
    nag_regsn_mult_linear_add_var(n, ip, q, tdq, p, wtptr, xe, &rss, tol,
                                  &fail);
    if (fail.code == NE_NOERROR)
      ip += 1;
    else if (fail.code == NE_NVAR_NOT_IND)
      printf(" * New variable not added * \n");
    else {
      printf("Error from nag_regsn_mult_linear_add_var (g02dec).\n%s\n",
             fail.message);
      exit_status = 1;
      goto END;
    }
  }
  rss = 0.0;
  /* 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, &rss, &df, b, se, cov, &svd,
                                  &rank, p, tol, &fail);
  if (fail.code != NE_NOERROR) {
    printf("Error from nag_regsn_mult_linear_upd_model (g02ddc).\n%s\n",
           fail.message);
    exit_status = 1;
    goto END;
  }

  printf("\n");
  if (svd)
    printf("Model not of full rank\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");

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

  return exit_status;
}