/* nag_rank_regsn (g08rac) Example Program.
 *
 * Copyright 2014 Numerical Algorithms Group.
 *
 * Mark 7, 2001.
 */

#include <stdio.h>
#include <nag.h>
#include <nag_stdlib.h>
#include <nagg08.h>

int main(void)
{

  /* Scalars */
  double        tol;
  Integer       exit_status, i, idist, p, j, nmax, ns, nsum;
  Integer       pdx, pdparvar;
  NagError      fail;
  Nag_OrderType order;

  /* Arrays */
  double        *eta = 0, *parest = 0, *parvar = 0, *vapvec = 0, *x = 0;
  double        *y = 0, *zin = 0;
  Integer       *irank = 0, *nv = 0;

#ifdef NAG_COLUMN_MAJOR
#define X(I, J)      x[(J-1)*pdx + I - 1]
#define PARVAR(I, J) parvar[(J-1)*pdparvar + I - 1]
  order = Nag_ColMajor;
#else
#define X(I, J)      x[(I-1)*pdx + J - 1]
#define PARVAR(I, J) parvar[(I-1)*pdparvar + J - 1]
  order = Nag_RowMajor;
#endif

  INIT_FAIL(fail);

  exit_status = 0;
  printf("nag_rank_regsn (g08rac) Example Program Results\n");

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

  /* Read number of samples, number of parameters to be fitted,
   * error distribution parameter and tolerance criterion for ties.
   */
  scanf("%ld%ld%ld%lf%*[^\n] ", &ns, &p, &idist,
         &tol);

  /* Allocate memory to nv only */
  if (!(nv = NAG_ALLOC(ns, Integer)))
    {
      printf("Allocation failure\n");
      exit_status = -1;
      goto END;
    }


  printf("\n");
  printf("Number of samples =%2ld\n", ns);
  printf("Number of parameters fitted =%2ld\n", p);
  printf("Distribution =%2ld\n", idist);
  printf("Tolerance for ties =%8.5f\n", tol);

  /* Read the number of observations in each sample. */

  for (i = 1; i <= ns; ++i)
    scanf("%ld", &nv[i - 1]);
  scanf("%*[^\n] ");

  nmax = 0;
  nsum = 0;
  for (i = 1; i <= ns; ++i)
    {
      nsum += nv[i - 1];
      nmax = MAX(nmax, nv[i - 1]);
    }
  if (nmax > 0 && nmax <= 100 && nsum > 0 && nsum <= 100)
    {
      /* Allocate memory */
      if (!(eta = NAG_ALLOC(nmax, double)) ||
          !(parest = NAG_ALLOC(4*p+1, double)) ||
          !(parvar = NAG_ALLOC((p+1)*p, double)) ||
          !(vapvec = NAG_ALLOC(nmax*(nmax+1)/2, double)) ||
          !(x = NAG_ALLOC(nsum * p, double)) ||
          !(y = NAG_ALLOC(nsum, double)) ||
          !(zin = NAG_ALLOC(nmax, double)) ||
          !(irank = NAG_ALLOC(nmax, Integer)))
        {
          printf("Allocation failure\n");
          exit_status = -1;
          goto END;
        }
#ifdef NAG_COLUMN_MAJOR
      pdx = nsum;
      pdparvar = p+1;
#else
      pdx = p;
      pdparvar = p;
#endif



      /* Read in observations and design matrices for each sample. */
      for (i = 1; i <= nsum; ++i)
        {
          scanf("%lf", &y[i - 1]);
          for (j = 1; j <= p; ++j)
            scanf("%lf", &X(i, j));
        }
      scanf("%*[^\n] ");

      /* nag_rank_regsn (g08rac).
       * Regression using ranks, uncensored data
       */
      nag_rank_regsn(order, ns, nv, y, p, x, pdx, idist, nmax, tol,
                     parvar, pdparvar, irank, zin, eta, vapvec, parest, &fail);
      if (fail.code != NE_NOERROR)
        {
          printf("Error from nag_rank_regsn (g08rac).\n%s\n",
                  fail.message);
          exit_status = 1;
          goto END;
        }

      printf("\n");
      printf("Score statistic\n");
      for (i = 1; i <= p; ++i)
        printf("%9.3f%s", parest[i - 1], i%2 == 0 || i == p?"\n":" ");
      printf("\n");

      printf("Covariance matrix of score statistic\n");
      for (j = 1; j <= p; ++j)
        {
          for (i = 1; i <= j; ++i)
            printf("%9.3f%s", PARVAR(i, j),
                    i%2 == 0 || i == j?"\n":" ");
        }
      printf("\n");

      printf("Parameter estimates\n");
      for (i = 1; i <= p; ++i)
        printf("%9.3f%s", parest[p + i - 1],
                i%2 == 0 || i == p?"\n":" ");
      printf("\n");

      printf("Covariance matrix of parameter estimates\n");
      for (i = 1; i <= p; ++i)

        {
          printf(" ");

          for (j = 1; j <= i; ++j)
            printf("%9.3f%s", PARVAR(i + 1, j),
                    j%2 == 0 || j == i?"\n":" ");
        }
      printf("\n");

      printf("Chi-squared statistic =%9.3f with%2ld d.f.\n",
              parest[p * 2], p);
      printf("\n");
      printf("Standard errors of estimates and\n");
      printf("approximate z-statistics\n");
      for (i = 1; i <= p; ++i)
        printf("%9.3f%14.3f\n", parest[2*p + 1 + i - 1],
                parest[p * 3 + 1 + i - 1]);
      printf("\n");
    }
 END:
  NAG_FREE(eta);
  NAG_FREE(parest);
  NAG_FREE(parvar);
  NAG_FREE(vapvec);
  NAG_FREE(x);
  NAG_FREE(y);
  NAG_FREE(zin);
  NAG_FREE(irank);
  NAG_FREE(nv);

  return exit_status;
}