//      g02ch Example Program Text
//      C# version, NAG Copyright 2008
using System;
using NagLibrary;
using System.Globalization;
using System.IO;
namespace NagDotNetExamples
{
  public class G02CHE
  {
    static string datafile = "ExampleData/g02che.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,   j;
        const int k1 = 3;
        const int n = 5;
        const int k = k1 - 1;
        double[,] coef = new double[k, 3];
        double[,] cz = new double[k, k];
        double[] result = new double[13];
        double[,] rz = new double[k1, k1];
        double[,] rznv = new double[k, k];
        double[,] sspz = new double[k1, k1];
        int ifail;
        Console.WriteLine("g02ch Example Program Results");
        //      Skip heading in data file
        sr.Reset();
        sr.Reset();
        for (i = 1; i <= k1; i++)
        {
          for (j = 1; j <= k1; j++)
          {
            sspz[i - 1, j - 1] = double.Parse(sr.Next(), CultureInfo.InvariantCulture);
          }
        }
        for (i = 1; i <= k1; i++)
        {
          for (j = 1; j <= k1; j++)
          {
            rz[i - 1, j - 1] = double.Parse(sr.Next(), CultureInfo.InvariantCulture);
          }
        }
        Console.WriteLine(" ");
        Console.WriteLine(" {0}", "Sums of squares and cross-products about zero:");
        for (j = 1; j <= k1; j++)
        {
          Console.Write(" {0,10}", j);
        }
        Console.WriteLine(" ");
        for (i = 1; i <= k1; i++)
        {
          Console.Write(" {0,4}", i);
          for (j = 1; j <= k1; j++)
          {
            Console.Write(" {0, 10:f4}", sspz[i - 1, j - 1]);
          }
          Console.WriteLine(" ");
        }
        Console.WriteLine(" ");
        Console.WriteLine(" {0}", "Correlation-like coefficients:");
        for (j = 1; j <= k1; j++)
        {
          Console.Write(" {0, 10}", j);
        }
        Console.WriteLine(" ");
        for (i = 1; i <= k1; i++)
        {
          Console.Write(" {0, 4}", i);
          for (j = 1; j <= k1; j++)
          {
            Console.Write(" {0, 10:f4}", rz[i - 1, j - 1]);
          }
          Console.WriteLine(" ");
        }
        Console.WriteLine(" ");
        // 
        G02.g02ch(n, k1, k, sspz, rz, result, coef, rznv, cz, out ifail);
        // 
        if (ifail != 0)
        {
          Console.WriteLine(" ");
          Console.WriteLine("** g02ch failed with ifail = {0,5}", ifail);
        }
        else
        {
          Console.WriteLine(" {0}", "Vble     Coef       Std err      t-value");
          for (i = 1; i <= k; i++)
          {
            Console.Write(" {0, 3}", i);
            for (j = 1; j <= 3; j++)
            {
              Console.Write(" {0, 12:f4}", coef[i - 1, j - 1]);
            }
            Console.WriteLine(" ");
          }
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "Analysis of regression table :-");
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "      Source        Sum of squares  D.F.    Mean square     F-value");
          Console.WriteLine(" ");
          Console.Write(" {0}", "Due to regression");
          for (i = 1; i <= 4; i++)
          {
            Console.Write(" {0, 12:f4}", result[i - 1]);
          }
          Console.WriteLine(" ");
          Console.Write(" {0}", "About  regression");
          for (i = 5; i <= 7; i++)
          {
            Console.Write(" {0, 12:f4}", result[i - 1]);
          }
          Console.WriteLine(" ");
          Console.Write(" {0}", "Total            ");
          for (i = 8; i <= 9; i++)
          {
            Console.Write(" {0, 12:f4}", result[i - 1]);
          }
          Console.WriteLine(" ");
          Console.WriteLine(" ");
          Console.WriteLine("  {0}{1,8:f4}", "Standard error of estimate =", result[9]);
          Console.WriteLine("  {0}{1,8:f4}", "Multiple correlation (R)   =", result[10]);
          Console.WriteLine("  {0}{1,8:f4}", "Determination (R squared)  =", result[11]);
          Console.WriteLine("  {0}{1,8:f4}", "Corrected R squared        =", result[12]);
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "Inverse of correlation matrix of independent variables:");
          for (j = 1; j <= k; j++)
          {
            Console.Write(" {0, 10}", j);
          }
          Console.WriteLine(" ");
          for (i = 1; i <= k; i++)
          {
            Console.Write(" {0, 4}", i);
            for (j = 1; j <= k; j++)
            {
              Console.Write(" {0, 10:f4}", rznv[i - 1, j - 1]);
            }
            Console.WriteLine(" ");
          }
          Console.WriteLine(" ");
          Console.WriteLine(" {0}", "Modified inverse matrix:");
          for (j = 1; j <= k; j++)
          {
            Console.Write(" {0, 10}", j);
          }
          Console.WriteLine(" ");
          for (i = 1; i <= k; i++)
          {
            Console.Write(" {0, 4}", i);
            for (j = 1; j <= k; j++)
            {
              Console.Write(" {0, 10:f4}", cz[i - 1, j - 1]);
            }
            Console.WriteLine(" ");
          }
          Console.WriteLine(" ");
        }
        // 
      }
      catch (Exception e)
      {
        Console.WriteLine(e.Message);
        Console.Write( "Exception Raised");
      }
    }
  }
}