[Quantproject-developers] QuantProject/b1_ADT/Econometrics LinearRegression.cs, 1.1, 1.2

[Glauco S. <gla...@us...>]

Update of /cvsroot/quantproject/QuantProject/b1_ADT/Econometrics
In directory sfp-cvsdas-2.v30.ch3.sourceforge.com:/tmp/cvs-serv12057/b1_ADT/Econometrics

Modified Files:
	LinearRegression.cs 
Log Message:
Computes a Linear Regression with covariance matrix and ANOVA (ANalysis Of VAriance)

Index: LinearRegression.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b1_ADT/Econometrics/LinearRegression.cs,v
retrieving revision 1.1
retrieving revision 1.2
diff -C2 -d -r1.1 -r1.2
*** LinearRegression.cs	27 Mar 2010 17:06:57 -0000	1.1
--- LinearRegression.cs	6 Jan 2011 18:31:18 -0000	1.2
***************
*** 3,7 ****
  
  LinearRegression.cs
! Copyright (C) 2010
  Glauco Siliprandi
  
--- 3,7 ----
  
  LinearRegression.cs
! Copyright (C) 2011
  Glauco Siliprandi
  
***************
*** 28,36 ****
  {
  	/// <summary>
! 	/// Computes a Linear Regression
  	/// </summary>
  	[Serializable]
  	public class LinearRegression : ILinearRegression
  	{
  		private double sumOfSquareResiduals;
  		private double centeredTotalSumOfSquares;
--- 28,38 ----
  {
  	/// <summary>
! 	/// Computes a Linear Regression with covariance matrix
! 	/// and ANOVA (ANalysis Of VAriance)
  	/// </summary>
  	[Serializable]
  	public class LinearRegression : ILinearRegression
  	{
+ 		private double[,] covarianceMatrix;		// (XTransposeX)^-1
  		private double sumOfSquareResiduals;
  		private double centeredTotalSumOfSquares;
***************
*** 81,97 ****
  			return xTransposeX;
  		}
! 		private double[] getXtransposeY( double[] y , double[,] X )
! 		{
! 			int n = y.Length;
! 			int k = X.GetLength( 1 );
! 			double[] xTransposeY = new double[ k ];
! 			for( int j = 0 ; j < k ; j++ )
! 			{
! 				xTransposeY[ j ] = 0;
! 				for( int t = 0 ; t < n ; t++ )
! 					xTransposeY[ j ] += X[ t , j ] * y[ t ];
! 			}
! 			return xTransposeY;
! 		}
  		
  		#region computeRSquare
--- 83,99 ----
  			return xTransposeX;
  		}
! //		private double[] getXtransposeY( double[] y , double[,] X )
! //		{
! //			int n = y.Length;
! //			int k = X.GetLength( 1 );
! //			double[] xTransposeY = new double[ k ];
! //			for( int j = 0 ; j < k ; j++ )
! //			{
! //				xTransposeY[ j ] = 0;
! //				for( int t = 0 ; t < n ; t++ )
! //					xTransposeY[ j ] += X[ t , j ] * y[ t ];
! //			}
! //			return xTransposeY;
! //		}
  		
  		#region computeRSquare
***************
*** 158,164 ****
  			this.runRegression_checkParameters( regressand , regressors );
  			double[,] xTransposeX = this.getXtransposeX( regressors );
! 			double[] xTransposeY = this.getXtransposeY( regressand , regressors );
! 			this.estimatedCoefficients = LinearSystemSolver.FindSolution(
! 				xTransposeX , xTransposeY );
  			this.computeCenteredRSquare( regressand , regressors );
  		}
--- 160,168 ----
  			this.runRegression_checkParameters( regressand , regressors );
  			double[,] xTransposeX = this.getXtransposeX( regressors );
! 			this.covarianceMatrix = PositiveDefiniteMatrix.GetInverse( xTransposeX );
! 			double[,] xTransposeXInverseXTranspose =
! 				Matrix.TransposeTheSecondMatrixAndMultiply( this.covarianceMatrix , regressors );
! //			double[] xTransposeY = this.getXtransposeY( regressand , regressors );
! 			this.estimatedCoefficients = Matrix.Multiply( xTransposeXInverseXTranspose , regressand );
  			this.computeCenteredRSquare( regressand , regressors );
  		}