/* nag_regsn_mult_linear_tran_model (g02dkc) 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]
#define C(I, J) c[(I) *tdc + J]
int main(void)
{
  Integer exit_status = 0, i, iconst, ip, j, m, n, rank, *sx = 0, tdc,
         tdq, tdx;
  double df, rss, tol;
  double *b = 0, *c = 0, *com_ar = 0, *cov = 0, *h = 0, *p = 0;
  double *q = 0, *res = 0, *se = 0, *wt = 0, *wtptr, *x = 0, *y = 0;
  char nag_enum_arg[40];
  Nag_Boolean svd, weight;
  Nag_IncludeMean mean;
  NagError fail;

  INIT_FAIL(fail);

  printf("nag_regsn_mult_linear_tran_model (g02dkc) 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);
  if (n >= 2 && 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)))
    {
      printf("Allocation failure\n");
      exit_status = -1;
      goto END;
    }
    tdx = m;
  }
  else {
    printf("Invalid n.\n");
    exit_status = 1;
    return exit_status;
  }
  if (weight) {
    wtptr = wt;
    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 {
    wtptr = (double *) 0;
    for (i = 0; i < n; i++) {
      for (j = 0; j < m; j++)
        scanf("%lf", &X(i, j));
      scanf("%lf", &y[i]);
    }
  }
  for (j = 0; j < m; j++)
    scanf("%" NAG_IFMT "", &sx[j]);
  scanf("%" NAG_IFMT "", &ip);

  if (!(b = NAG_ALLOC(ip, double)) ||
      !(c = NAG_ALLOC((ip) * (ip), double)) ||
      !(cov = NAG_ALLOC(ip * (ip + 1) / 2, double)) ||
      !(p = NAG_ALLOC(ip * (ip + 2), double)) ||
      !(q = NAG_ALLOC(n * (ip + 1), double)) ||
      !(se = NAG_ALLOC(ip, double)) ||
      !(com_ar = NAG_ALLOC(4 * ip * ip + 5 * (ip - 1), double)))
  {
    printf("Allocation failure\n");
    exit_status = -1;
    goto END;
  }
  tdq = ip + 1;
  tdc = ip;

  /* Set tolerance */
  tol = 0.00001e0;
  /* Find initial estimates using nag_regsn_mult_linear (g02dac) */
  /* 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("Estimates from g02dac\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");
  /*
   *    Input constraints and call nag_regsn_mult_linear_tran_model (g02dkc)
   */
  iconst = ip - rank;
  for (i = 0; i < ip; ++i)
    for (j = 0; j < iconst; ++j)
      scanf("%lf", &C(i, j));

  /* nag_regsn_mult_linear_tran_model (g02dkc).
   * Estimates of parameters of a general linear regression
   * model for given constraints
   */
  nag_regsn_mult_linear_tran_model(ip, iconst, p, c, tdc, b, rss, df, se, cov,
                                   &fail);
  if (fail.code != NE_NOERROR) {
    printf("Error from nag_regsn_mult_linear_tran_model (g02dkc).\n%s\n",
           fail.message);
    exit_status = 1;
    goto END;
  }

  printf("\n");
  printf("Estimates from nag_regsn_mult_linear_tran_model (g02dkc) using "
         "constraints\n\n");
  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(h);
  NAG_FREE(res);
  NAG_FREE(wt);
  NAG_FREE(x);
  NAG_FREE(y);
  NAG_FREE(sx);
  NAG_FREE(b);
  NAG_FREE(c);
  NAG_FREE(cov);
  NAG_FREE(p);
  NAG_FREE(q);
  NAG_FREE(se);
  NAG_FREE(com_ar);

  return exit_status;
}