/* nag_regsn_mult_linear_delete_var (g02dfc) Example Program.
 *
 * Copyright 1991 Numerical Algorithms Group.
 *
 * Mark 2, 1991.
 * Mark 8 revised, 2004.
 */

#include <nag.h>
#include <nagx04.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(int argc, char *argv[])
{
  FILE            *fpin, *fpout;
  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);

  /* Check for command-line IO options */
  fpin = nag_example_file_io(argc, argv, "-data", NULL);
  fpout = nag_example_file_io(argc, argv, "-results", NULL);
  fprintf(fpout, "nag_regsn_mult_linear_delete_var (g02dfc) Example Program "
          "Results\n");
  /* Skip heading in data file */
  fscanf(fpin, "%*[^\n]");
  fscanf(fpin, "%ld %ld", &n, &m);
  fscanf(fpin, " %s", 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);
  fscanf(fpin, " %s", 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)))
        {
          fprintf(fpout, "Allocation failure\n");
          exit_status = -1;
          goto END;
        }
      tdx = m;
      tdq = ipmax+1;
    }
  else
    {
      fprintf(fpout, "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)
            fscanf(fpin, "%lf", &X(i, j));
          fscanf(fpin, "%lf%lf", &y[i], &wt[i]);
        }
    }
  else
    {
      for (i = 0; i < n; ++i)
        {
          for (j = 0; j < m; ++j)
            fscanf(fpin, "%lf", &X(i, j));
          fscanf(fpin, "%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)
    {
      fprintf(fpout, "Error from nag_regsn_mult_linear (g02dac).\n%s\n",
              fail.message);
      exit_status = 1;
      goto END;
    }

  fprintf(fpout, "Results from full model\n");
  if (svd)
    fprintf(fpout, "Model not of full rank\n\n");
  fprintf(fpout, "Residual sum of squares = %13.4e\n", rss);
  fprintf(fpout, "Degrees of freedom = %3.1f\n\n", df);
  while (fscanf(fpin, "%ld", &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)
            {
              fprintf(fpout,
                      "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)
            fprintf(fpout, "No terms left in model\n");
          else
            {
              fprintf(fpout, "Variable %4ld 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)
                {
                  fprintf(fpout, "Error from nag_regsn_mult_linear_upd_model "
                          "(g02ddc).\n%s\n", fail.message);
                  exit_status = 1;
                  goto END;
                }

              fprintf(fpout, "Residual sum of squares = %13.4e\n", rss);
              fprintf(fpout, "Degrees of freedom = %3.1f\n\n", df);
              fprintf(fpout, "Parameter estimate   Standard error\n\n");
              for (j = 0; j < ip; j++)
                fprintf(fpout, "%15.4e%15.4e\n", b[j], se[j]);
            }
        }
    }
 END:
  if (fpin != stdin) fclose(fpin);
  if (fpout != stdout) fclose(fpout);
  if (h) NAG_FREE(h);
  if (res) NAG_FREE(res);
  if (wt) NAG_FREE(wt);
  if (x) NAG_FREE(x);
  if (y) NAG_FREE(y);
  if (sx) NAG_FREE(sx);
  if (b) NAG_FREE(b);
  if (cov) NAG_FREE(cov);
  if (p) NAG_FREE(p);
  if (q) NAG_FREE(q);
  if (se) NAG_FREE(se);
  if (com_ar) NAG_FREE(com_ar);
  return exit_status;
}