/* nag_simple_linear_regression (g02cac) Example Program.
 *
 * Copyright 1992 Numerical Algorithms Group.
 *
 * Mark 3, 1992.
 * Mark 8 revised, 2004.
 */

#include <nag.h>
#include <nagx04.h>
#include <stdio.h>
#include <nag_stdlib.h>
#include <nagg02.h>

int main(int argc, char *argv[])
{
  FILE          *fpin, *fpout;
  Integer       exit_status = 0, i, n;
  Nag_SumSquare mean;
  Nag_Boolean   weight;
  char          nag_enum_arg[40];
  double        a, b, df, err_a, err_b, rsq, rss;
  double        *wt = 0, *wtptr, *x = 0, *y = 0;
  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_simple_linear_regression (g02cac) Example Program Results\n");
  /* Skip heading in data file */
  fscanf(fpin, "%*[^\n]");
  fscanf(fpin, " %s", nag_enum_arg);
  /* nag_enum_name_to_value(x04nac).
   * Converts NAG enum member name to value
   */
  mean = (Nag_SumSquare) nag_enum_name_to_value(nag_enum_arg);
  fscanf(fpin, " %s", nag_enum_arg);
  weight = (Nag_Boolean) nag_enum_name_to_value(nag_enum_arg);
  fscanf(fpin, "%ld", &n);
  if (n >= (mean == Nag_AboutMean?2:1))
    {
      if (!(x = NAG_ALLOC(n, double)) ||
          !(y = NAG_ALLOC(n, double)) ||
          !(wt = NAG_ALLOC(n, double)))
        {
          fprintf(fpout, "Allocation failure\n");
          exit_status = -1;
          goto END;
        }
    }
  else
    {
      fprintf(fpout, "Invalid n.\n");
      exit_status = 1;
      return exit_status;
    }

  if (weight)
    {
      wtptr = wt;
      for (i = 0; i < n; ++i)
        fscanf(fpin, "%lf%lf%lf", &x[i], &y[i], &wt[i]);
    }
  else
    {
      wtptr = (double *) 0;
      for (i = 0; i < n; ++i)
        fscanf(fpin, "%lf%lf", &x[i], &y[i]);
    }

  /* nag_simple_linear_regression (g02cac).
   * Simple linear regression with or without a constant term,
   * data may be weighted
   */
  nag_simple_linear_regression(mean, n, x, y, wtptr, &a, &b, &err_a, &err_b,
                               &rsq, &rss, &df, &fail);
  if (fail.code != NE_NOERROR)
    {
      fprintf(fpout, "Error from nag_simple_linear_regression (g02cac).\n%s\n",
              fail.message);
      exit_status = 1;
      goto END;
    }

  if (mean == Nag_AboutMean)
    {
      fprintf(fpout, "\nRegression constant a = %6.4f\n\n", a);
      fprintf(fpout, "Standard error of the regression constant a = %6.4f\n\n",
              err_a);
    }

  fprintf(fpout, "Regression coefficient b = %6.4f\n\n", b);
  fprintf(fpout, "Standard error of the regression coefficient b = %6.4f\n\n",
          err_b);

  fprintf(fpout, "The regression coefficient of determination = %6.4f\n\n",
          rsq);
  fprintf(fpout, "The sum of squares of the residuals about the "
          "regression = %6.4f\n\n", rss);
  fprintf(fpout, "Number of degrees of freedom about the "
          "regression = %6.4f\n\n", df);

 END:
  if (fpin != stdin) fclose(fpin);
  if (fpout != stdout) fclose(fpout);
  if (x) NAG_FREE(x);
  if (y) NAG_FREE(y);
  if (wt) NAG_FREE(wt);

  return exit_status;
}