/* nag_robust_corr_estim (g02hkc) Example Program.
 *
 * Copyright 1996 Numerical Algorithms Group.
 *
 * Mark 4, 1996.
 * 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-1)*tdx + J-1]
int main(int argc, char *argv[])
{
  FILE     *fpin, *fpout;
  char     *outfile = 0;
  Integer  exit_status = 0, i, iter, j, k, l1, l2, m, max_iter, n, print_iter;
  Integer  tdx;
  NagError fail;
  double   *cov = 0, eps, *theta = 0, tol, *x = 0;

  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);
  (void) nag_example_file_io(argc, argv, "-nag_write", &outfile);

  fprintf(fpout, "nag_robust_corr_estim (g02hkc) Example Program Results\n\n");

  /* Skip heading in data file */
  fscanf(fpin, "%*[^\n]\n");

  /* Read in the dimensions of X */
  fscanf(fpin, "%ld %ld %*[^\n]\n", &n, &m);

  if (n > 1 && (m >= 1 && m <= n))
    {
      if (!(x = NAG_ALLOC((n)*(m), double)) ||
          !(theta = NAG_ALLOC(m, double)) ||
          !(cov = NAG_ALLOC(m*(m+1)/2, double)))
        {
          fprintf(fpout, "Allocation failure\n");
          exit_status = -1;
          goto END;
        }
      tdx = m;
    }
  else
    {
      fprintf(fpout, "Invalid n or m.\n");
      exit_status = 1;
      return exit_status;
    }
  /* Read in the x matrix */
  for (i = 1; i <= n; ++i)
    {
      for (j = 1; j <= m; ++j)
        fscanf(fpin, "%lf", &X(i, j));
      fscanf(fpin, "%*[^\n]\n");
    }

  /* Read in value of eps */
  fscanf(fpin, "%lf%*[^\n]\n", &eps);

  /* Set up remaining parameters */
  max_iter = 100;
  tol = 5e-5;

  /* Set print_iter to positive value for iteration moiteroring */
  print_iter = 1;
  /* nag_robust_corr_estim (g02hkc).
   * Robust estimation of a correlation matrix, Huber's weight
   * function
   */
  if (outfile) fclose(fpout);
  nag_robust_corr_estim(n, m, x, tdx, eps, cov, theta, max_iter, print_iter,
                        outfile, tol, &iter, &fail);
  if (outfile && !(fpout = fopen(outfile, "a")))
    {
      exit_status = 2;
      goto END;
    }
  if (fail.code != NE_NOERROR)
    {
      fprintf(fpout, "Error from nag_robust_corr_estim (g02hkc).\n%s\n",
              fail.message);
      exit_status = 1;
      goto END;
    }

  fprintf(fpout,
          "\n\nnag_robust_corr_estim (g02hkc) required %ld iterations "
          "to converge\n\n", iter);
  fprintf(fpout, "Covariance matrix\n");
  l2 = 0;
  for (j = 1; j <= m; ++j)
    {
      l1 = l2 + 1;
      l2 += j;
      for (k = l1; k <= l2; ++k)
        fprintf(fpout, "%10.3f", cov[k - 1]);
      fprintf(fpout, "\n");
    }
  fprintf(fpout, "\n\ntheta\n");
  for (j = 1; j <= m; ++j)
    fprintf(fpout, "%10.3f\n", theta[j - 1]);

 END:
  if (fpin != stdin) fclose(fpin);
  if (fpout != stdout) fclose(fpout);
  if (x) NAG_FREE(x);
  if (theta) NAG_FREE(theta);
  if (cov) NAG_FREE(cov);
  return exit_status;
}