/* nag_rank_regsn_censored (g08rbc) Example Program.
 *
 * Copyright 2001 Numerical Algorithms Group.
 *
 * Mark 7, 2001.
 */

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

int main(void)
{

  /* Scalars */
  double gamma, tol;
  Integer exit_status, i, 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, *y=0, *zin=0;
  Integer *icen=0, *irank=0, *iwa=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;
  Vprintf("g08rbc Example Program Results\n");

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

  /* Read number of samples, number of parameters to be fitted, */
  /* distribution power parameter and tolerance criterion for ties. */

  Vscanf("%ld%ld%lf%lf%*[^\n] ", &ns, &p, &gamma, &tol);
  Vprintf("\n");

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

  Vprintf("Number of samples =%2ld\n", ns);
  Vprintf("Number of parameters fitted =%2ld\n", p);
  Vprintf("Distribution power parameter =%10.5f\n", gamma);

  Vprintf("Tolerance for ties =%10.5f\n", tol);

  Vprintf("\n");
  /* Read the number of observations in each sample */

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

  nmax = 0;
  nsum = 0;
  for (i = 1; i <= ns; ++i)
    {
      nsum += nv[i - 1];
      nmax = MAX(nmax,nv[i - 1]);
    }

  /* Allocate memory */
  if ( !(eta = NAG_ALLOC(nmax, double)) ||
       !(parest = NAG_ALLOC(4*p+1, double)) ||
       !(parvar = NAG_ALLOC(7 * 6, 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)) ||
       !(icen = NAG_ALLOC(nsum, Integer)) ||
       !(irank = NAG_ALLOC(nmax, Integer)) ||
       !(iwa = NAG_ALLOC(400, Integer)) )
    {
      Vprintf("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, design matrix and censoring variable */

  for (i = 1; i <= nsum; ++i)
    {
      Vscanf("%lf", &y[i - 1]);

      for (j = 1; j <= p; ++j)
        {
          Vscanf("%lf", &X(i,j));
        }
      Vscanf("%ld", &icen[i - 1]);
    }
  Vscanf("%*[^\n] ");

  g08rbc(order, ns, nv, y, p, x, pdx, icen, gamma,
         nmax, tol, parvar, pdparvar, irank, zin, eta, vapvec,
         parest, &fail);
  if (fail.code != NE_NOERROR)
    {
      Vprintf("Error from g08rbc.\n%s\n", fail.message);
      exit_status = 1;
      goto END;
    }

  Vprintf("Score statistic\n");

  for (i = 1; i <= p; ++i)
    Vprintf("%9.3f\n", parest[i - 1]);
  Vprintf("\n");

  Vprintf("Covariance matrix of score statistic\n");
  for (j = 1; j <= p; ++j)
    {
      for (i = 1; i <= j; ++i)
        Vprintf("%9.3f\n", PARVAR(i,j));
      Vprintf("\n");
    }


  Vprintf("Parameter estimates\n");
  for (i = 1; i <= p; ++i)
    Vprintf("%9.3f\n", parest[p + i - 1]);
  Vprintf("\n");
  Vprintf("Covariance matrix of parameter estimates\n");
  for (i = 1; i <= p; ++i)
    {
      for (j = 1; j <= i; ++j)
        Vprintf("%9.3f\n", PARVAR(i + 1,j));
      Vprintf("\n");
    }


  Vprintf("Chi-squared statistic =%9.3f with%2ld d.f.\n", parest[p * 2], p);
  Vprintf("\n");

  Vprintf("Standard errors of estimates and\n");
  Vprintf("approximate z-statistics\n");

  for (i = 1; i <= p; ++i)
    Vprintf("%9.3f%14.3f\n", parest[2*p + 1 + i - 1], parest[p * 3 + 1 + i - 1]);
 END:
  if (eta) NAG_FREE(eta);
  if (parest) NAG_FREE(parest);
  if (parvar) NAG_FREE(parvar);
  if (vapvec) NAG_FREE(vapvec);
  if (x) NAG_FREE(x);
  if (y) NAG_FREE(y);
  if (zin) NAG_FREE(zin);
  if (icen) NAG_FREE(icen);
  if (irank) NAG_FREE(irank);
  if (iwa) NAG_FREE(iwa);
  if (nv) NAG_FREE(nv);

  return exit_status;
}