C:/Documents and Settings/Stephen/Desktop/Biostatistics Library and Program/Biostatistics/ChiSquaredArray.cs

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using System;
using System.Windows.Forms;

namespace StephenAshley.Biostatistics
{
   using NUMBER = Decimal;

   public class ChiSquaredArray
   {
      protected ChiSquaredArray() { }

      public ChiSquaredArray(Int32 columns, Int32 rows)
      {
         outcomesArray = new Outcome[(iColumns = columns) + 1, (iRows = rows) + 1];
         iColumns = columns;
         iRows = rows;
      }
      protected Outcome[,] outcomesArray;

      private Int32 iColumns;
      private Int32 iRows;

      public void Add(Int32 column, Int32 row, Int32 observed)
      {
         if (column < 0)
            throw new BiostatisticsException(
               "column value in Add method of ChiSquaredArray less than 0.");

         if (column > iColumns)
            throw new BiostatisticsException(
               "column value in Add method of ChiSquaredArray greater than iColumns.");

         if (row < 0)
            throw new BiostatisticsException(
               "row value in Add method of ChiSquaredArray less than 0.");

         if (row > iRows)
            throw new BiostatisticsException(
               "row value in Add method of ChiSquaredArray greater than iRows.");

         outcomesArray[column, row] = new Outcome(observed, 0);
         FillArray();
      }

      public void Add(Int32 column, Int32 row, Int32 observed, NUMBER expected)
      {
         outcomesArray[column, row].decExpected = expected;
         Add(column, row, observed);
      }

      public void Add(Int32 column, Int32 row, Outcome outcome)
      {
         Add(column, row, outcome.iObserved, outcome.decExpected);
      }

      public void Add(Int32 iCols, Int32 iRows, TextBox[,] pitb)
      {
         for (Int32 i = 0; i < iCols; i++)
            for (Int32 j = 0; j < iRows; j++)
               Add(i, j, Convert.ToInt32(pitb[i, j].Text));
      }
      public NUMBER ChiSquared()
      {
         return outcomesArray[iColumns, iRows].decDifferenceSquared;
      }

      public Int32 DegreesOfFreedom()
      {return (iColumns - 1) * (iRows - 1);}

      public virtual NUMBER p()
      {return Convert.ToDecimal(Distributions.ProbabilityChiSq(Convert.ToDouble(ChiSquared()), 
         DegreesOfFreedom()));}

      private void FillArray()
      {
         // Compute the sum of each column.
         for (Int32 i = 0; i < iColumns; i++)
         {
            Int32 iTotal = 0;
            for (Int32 j = 0; j < iRows; j++)
            {
               iTotal += outcomesArray[i, j].iObserved;
            }
            outcomesArray[i, iRows].iObserved = iTotal;
         }

         // Compute the sum of each row.
         for (Int32 i = 0; i < iRows; i++)
         {
            Int32 iTotal = 0;
            for (Int32 j = 0; j < iColumns; j++)
               iTotal += outcomesArray[j, i].iObserved;
            outcomesArray[iColumns, i].iObserved = iTotal;
         }

         // Compute the total of all observations.
         Int32 iGrandTotal = 0;
         for (Int32 i = 0; i < iColumns; i++)
         {
            iGrandTotal += outcomesArray[i, iRows].iObserved;
         }

         outcomesArray[iColumns, iRows].iObserved = iGrandTotal;

         NUMBER decYatesCorrection = 0.0m;
         if (iColumns == 2 && iRows == 2)
            decYatesCorrection = 0.5m;

         // Compute the expected values and difference squared for each cell.
         for (Int32 i = 0; i < iColumns; i++)
            for (Int32 j = 0; j < iRows; j++)
            {
               if (outcomesArray[iColumns, iRows].iObserved != 0)
               outcomesArray[i, j].decExpected = Convert.ToDecimal(
                  outcomesArray[iColumns, j].iObserved * outcomesArray[i, iRows].iObserved) 
                  / outcomesArray[iColumns, iRows].iObserved;

               NUMBER decDifference = DecMath.Abs( outcomesArray[i,j].decExpected -
                  outcomesArray[i,j].iObserved) - decYatesCorrection;
               outcomesArray[i, j].decDifferenceSquared = decDifference * decDifference;
            }

         NUMBER decChiSquared = 0.0m;
         for (Int32 i = 0; i < iColumns; i++)
            for (Int32 j = 0; j < iRows; j++)
            {
               if (outcomesArray[i,j].decExpected != 0.0m)
               decChiSquared += outcomesArray[i, j].decDifferenceSquared /
                  outcomesArray[i, j].decExpected;
            }
         outcomesArray[iColumns, iRows].decDifferenceSquared = decChiSquared;
      }
   }


   public struct Outcome
   {
      public Outcome(Int32 observed, Int32 expected)
      {
         iObserved = observed;
         decExpected = expected;
         decDifferenceSquared = 0.0m;
      }
      public Int32 iObserved;
      public NUMBER decExpected;
      public NUMBER decDifferenceSquared;
   }
}

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