//      g02kb Example Program Text
//      C# version, NAG Copyright 2008
using System;
using NagLibrary;
using System.Globalization;
using System.IO;
namespace NagDotNetExamples
{
  public class G02KBE
  {
    static string datafile = "ExampleData/g02kbe.d";
    static void Main(String[] args)
    {
      if (args.Length == 1)
      {
        datafile = args[0];
      }
      StartExample();
    }
    public static void StartExample()
    {
      try
      {
        DataReader sr = new DataReader(datafile);
        int i,   ip,   ip1,   j,   lh,   lpec,   m,   n,   pl,   wantb,   wantvf;
        int ldb, tdb, ldpe, tdpe, ldvf, tdvf;
        // 
        int ifail;
        Console.WriteLine("g02kb Example Program Results");
        // 
        //      Skip heading in data file
        sr.Reset();
        // 
        //      Read in the problem size information
        sr.Reset();
        n = int.Parse(sr.Next());
        m = int.Parse(sr.Next());
        lh = int.Parse(sr.Next());
        lpec = int.Parse(sr.Next());
        wantb = int.Parse(sr.Next());
        wantvf = 1;
        ldpe = 5;
        double[] h = new double[lh];
        double[] nep = new double[lh];
        double[,] x = new double[n, m];
        double[] y = new double[n];
        int[] isx = new int[m];
        string[] pec = new string[lpec];
        // 
        //      Check array sizes
        if (n < 1 || m > n || lh < 1 || ldpe < lpec)
        {
          Console.Write("   ** Problem size is too small or inconsistent");
          goto L160;
        }
        // 
        //      Read in the data
        if (lpec > 0)
        {
          sr.Reset();
          for (i = 1; i <= lpec; i++)
          {
            pec[i - 1] = sr.Next();
          }
        }
        for (i = 1; i <= n; i++)
        {
          sr.Reset();
          for (j = 1; j <= m; j++)
          {
            x[i - 1, j - 1] = double.Parse(sr.Next(), CultureInfo.InvariantCulture);
          }
          y[i - 1] = double.Parse(sr.Next(), CultureInfo.InvariantCulture);
        }
        // 
        //      Read in the isx flags
        sr.Reset();
        for (i = 1; i <= m; i++)
        {
          isx[i - 1] = int.Parse(sr.Next());
        }
        // 
        //      Read in the ridge coefficients
        sr.Reset();
        for (i = 1; i <= lh; i++)
        {
          h[i - 1] = double.Parse(sr.Next(), CultureInfo.InvariantCulture);
        }
        // 
        //      Total number of variables
        ip = 0;
        for (j = 1; j <= m; j++)
        {
          if (isx[j - 1] == 1)
          {
            ip = ip + 1;
          }
        }
        if (wantb != 0)
        {
          ldb = ip + 1;
          tdb = lh;
        }
        else
        {
          ldb = 1;
          tdb = 1;
        }
        if (wantvf != 0) 
        {
          ldvf = ip;
          tdvf = lh;
        }
        else
        {
          ldvf = 0;
          tdvf = 0;
        }
        if (lpec>0) 
        {
          ldpe = lpec;
          tdpe = lh;
        }
        else
        {
          ldpe = 0;
          tdpe = 0;
        }
        double[,] pe = new double[ldpe, tdpe];
        double[,] vf = new double[ldvf, tdvf];
        double[,] b = new double[ldb, tdb];
        // 
        //      Output the variance inflation factors and parameter estimates
        //      (original scalings)
        // 
        //      Run the analysis
        G02.g02kb(  n, m, x, isx, ip, y, lh ,h, nep, wantb, b, wantvf, vf, lpec,pec, pe, out ifail);
        if (ifail != 0)
        {
          Console.WriteLine("** g02kb failed with ifail = {0,5}", ifail);
          goto L160;
        }
        //      Output results
        ip1 = ip - 1;
        // 
        //      Summaries
        Console.WriteLine("{0}{1,10}", "Number of parameters used = ", ip + 1);
        Console.WriteLine(" {0}", "Effective number of parameters (NEP):");
        Console.WriteLine(" {0}", "   Ridge   ");
        Console.WriteLine(" {0} {1}", "   Coeff.  ", "NEP");
        for (i = 1; i <= lh; i++)
        {
          Console.WriteLine("{0,10:f4}{1,10:f4}", h[i - 1], nep[i - 1]);
        }
        // 
        //      Parameter estimates
        if (wantb != 0)
        {
          Console.WriteLine(" ");
          if (wantb == 1)
          {
            Console.WriteLine(" {0}", "Parameter Estimates (Original scalings)");
          }
          else
          {
            Console.WriteLine(" {0}", "Parameter Estimates (Standarised)");
          }
          pl = Math.Min(ip, 4);
          Console.WriteLine(" {0}", "  Ridge  ");
          Console.WriteLine(" ");
          Console.Write(" {0}", "   Coeff.  ");
          Console.Write(" {0}", " Intercept ");
          for (i = 1; i <= pl; i++)
          {
            Console.Write(" {0}", i);
          }
          Console.WriteLine(" ");
          if (pl < ip1)
          {
            for (i = pl + 1; i <= ip1; i++)
            {
              Console.Write(" {0}", i);
            }
            Console.WriteLine(" ");
          }
          pl = Math.Min(ip + 1, 5);
          for (i = 1; i <= lh; i++)
          {
            Console.Write(" {0, 10:f4}", h[i - 1]);
            for (j = 1; j <= pl; j++)
            {
              Console.Write(" {0, 10:f4}", b[j - 1, i - 1]);
            }
            Console.WriteLine(" ");
            if (pl < ip)
            {
              for (j = pl + 1; j <= ip; j++)
              {
                Console.Write(" {0, 10:f4}", b[j - 1, i - 1]);
              }
              Console.WriteLine(" ");
            }
          }
        }
        // 
        //      Variance inflation factors
        if (wantvf != 0)
        {
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "Variance Inflation Factors");
          pl = Math.Min(ip, 5);
          Console.Write(" {0}", "  Ridge  ");
          Console.WriteLine(" ");
          Console.Write(" {0}", "  Coeff.  ");
          for (i = 1; i <= pl; i++)
          {
            Console.Write(" {0, 10}", i);
          }
          Console.WriteLine(" ");
          if (pl < ip)
          {
            for (i = pl + 1; i <= ip; i++)
            {
              Console.Write(" {0, 10}", i);
            }
            Console.WriteLine(" ");
          }
          for (i = 1; i <= lh; i++)
          {
            Console.Write(" {0, 10:f4}", h[i - 1]);
            for (j = 1; j <= pl; j++)
            {
              Console.Write(" {0, 10:f4}", vf[j - 1, i - 1]);
            }
            Console.WriteLine(" ");
            if (pl < ip)
            {
              for (j = pl + 1; j <= ip; j++)
              {
                Console.Write(" {0, 10:f4}", vf[j - 1, i - 1]);
              }
              Console.WriteLine(" ");
            }
          }
        }
        // 
        //      Prediction error criterion
        if (lpec > 0)
        {
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "Prediction error criterion");
          pl = Math.Min(lpec, 5);
          Console.Write(" {0}", "  Ridge  ");
          Console.WriteLine(" ");
          Console.Write(" {0}", "  Coeff.  ");
          for (i = 1; i <= pl; i++)
          {
            Console.Write(" {0, 10}", i);
          }
          Console.WriteLine(" ");
          if (pl < lpec)
          {
            for (i = pl + 1; i <= lpec; i++)
            {
              Console.Write(" {0, 10}", i);
            }
            Console.WriteLine(" ");
          }
          for (i = 1; i <= lh; i++)
          {
            Console.Write(" {0, 10:f4}", h[i - 1]);
            for (j = 1; j <= pl; j++)
            {
              Console.Write(" {0, 10:f4}", pe[j - 1, i - 1]);
            }
            Console.WriteLine(" ");
            if (pl < ip)
            {
              for (j = pl + 1; j <= ip; j++)
              {
                Console.Write(" {0, 10:f4}", pe[j - 1, i - 1]);
              }
              Console.WriteLine(" ");
            }
          }
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "Key:");
          for (i = 1; i <= lpec; i++)
          {
            if (pec[i - 1] == "L")
            {
              Console.WriteLine("  {0,5}  {1}", i, "Leave one out cross-validation");
            }
            else if (pec[i - 1] == "G")
            {
              Console.WriteLine("  {0,5}  {1}", i, "Generalised cross-validation");
            }
            else if (pec[i - 1] == "U")
            {
              Console.WriteLine("  {0,5}  {1}", i, "Unbiased estimate of variance");
            }
            else if (pec[i - 1] == "F")
            {
              Console.WriteLine("  {0,5}  {1}", i, "Final prediction error");
            }
            else if (pec[i - 1] == "B")
            {
              Console.WriteLine("  {0,5}  {1}", i, "Bayesian information criterion");
            }
          }
        }
        // 
        L160: ;
        // 
      }
      catch (Exception e)
      {
        Console.WriteLine(e.Message);
        Console.Write( "Exception Raised");
      }
    }
  }
}