/* nag_regsn_mult_linear_delete_var (g02dfc) 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]
int main(void)
{
  Integer exit_status = 0, i, indx, ip, ipmax, j, m, n, rank, *sx = 0,
         tdq, tdx;
  char nag_enum_arg[40];
  double *b = 0, *com_ar = 0, *cov = 0, df, *h = 0, *p = 0, *q = 0;
  double *res = 0, rss, *se = 0, tol, *wt = 0, *wtptr, *x = 0, *y = 0;
  Nag_Boolean svd, weight;
  Nag_IncludeMean mean;
  NagError fail;

  INIT_FAIL(fail);

  printf("nag_regsn_mult_linear_delete_var (g02dfc) 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);
  ipmax = m + 1;
  if (n >= 1 && 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)) ||
        !(b = NAG_ALLOC(ipmax, double)) ||
        !(cov = NAG_ALLOC(ipmax * (ipmax + 1) / 2, double)) ||
        !(p = NAG_ALLOC(ipmax * (ipmax + 2), double)) ||
        !(q = NAG_ALLOC((n) * (ipmax + 1), double)) ||
        !(se = NAG_ALLOC(ipmax, double)) ||
        !(com_ar = NAG_ALLOC(5 * (ipmax - 1) + ipmax * ipmax, 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", &y[i], &wt[i]);
    }
  }
  else {
    for (i = 0; i < n; ++i) {
      for (j = 0; j < m; ++j)
        scanf("%lf", &X(i, j));
      scanf("%lf", &y[i]);
    }
  }
  for (i = 0; i < m; ++i)
    sx[i] = 1;
  ip = m;
  if (mean == Nag_MeanInclude)
    ip += 1;
  /* Set tolerance  */
  tol = 0.00001e0;
  /* 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("Results from full model\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);
  while (scanf("%" NAG_IFMT "", &indx) != EOF)
  {
    if (indx != 0) {
      /* nag_regsn_mult_linear_delete_var (g02dfc).
       * Delete an independent variable from a general linear
       * regression model
       */
      nag_regsn_mult_linear_delete_var(ip, q, tdq, indx, &rss, &fail);
      if (fail.code != NE_NOERROR) {
        printf("Error from nag_regsn_mult_linear_delete_var (g02dfc)."
               "\n%s\n", fail.message);
        exit_status = 1;
        goto END;
      }

      ip = ip - 1;
      if (ip == 0)
        printf("No terms left in model\n");
      else {
        printf("Variable %4" NAG_IFMT " dropped\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, &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("Residual sum of squares = %13.4e\n", rss);
        printf("Degrees of freedom = %3.1f\n\n", df);
        printf("Parameter estimate   Standard error\n\n");
        for (j = 0; j < ip; j++)
          printf("%15.4e%15.4e\n", b[j], se[j]);
      }
    }
  }
END:
  NAG_FREE(h);
  NAG_FREE(res);
  NAG_FREE(wt);
  NAG_FREE(x);
  NAG_FREE(y);
  NAG_FREE(sx);
  NAG_FREE(b);
  NAG_FREE(cov);
  NAG_FREE(p);
  NAG_FREE(q);
  NAG_FREE(se);
  NAG_FREE(com_ar);
  return exit_status;
}