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QRRegressionCalculation Class

Class QRRegressionCalculation computes linear regression parameters by the method of least squares using a QR decomposition.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreQRRegressionCalculation

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.4
Syntax
[SerializableAttribute]
public class QRRegressionCalculation : IRegressionCalculation, 
	ICloneable

The QRRegressionCalculation type exposes the following members.

Constructors
  NameDescription
Public methodQRRegressionCalculation
Constrcts a QRRegressionCalculation instance with all sizes equal to zero.
Public methodQRRegressionCalculation(DoubleMatrix)
Constructs a QRRegressionCalculation instance from the given matrix.
Public methodQRRegressionCalculation(DoubleMatrix, Double)
Constructs a QRRegressionCalculation instance from the given matrix. The specified tolerance is used in computing the numerical rank of the matrix.
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Properties
  NameDescription
Public propertyCols
Gets the number of columns in the matrix.
Public propertyIsGood
Returns true if the QR decomposition may be used to solve least squares problems; otherwise false.
Public propertyRank
Gets the numerical rank of the matrix.
Public propertyRankAvailable
Returns the rank if it was calculated as a byproduct of the parameter calculation.
Public propertyRows
Gets the number of rows in the matrix.
Public propertyTolerance
Gets and sets the tolerance used for computing the numerical rank of the regression matrix.
Public propertyXTXInv
Gets the matrix formed by taking the inverse of the product of the transpose of the regression matrix with itself, if available.
Public propertyXTXInvAvailable
Gets a boolean value indicating whether or not the matrix formed by taking the inverse of the product of the transpose of the regression matrix with itself is available.
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Methods
  NameDescription
Public methodCalculateParameters(DoubleMatrix, DoubleVector)
Calculates the parameters for the regression using a QR decomposition of the regression matrix to solve the least squares problem.
Public methodCalculateParameters(DoubleMatrix, DoubleVector, Boolean)
Calculates the parameters for the regression using a QR decomposition of the regression matrix to solve the least squares problem.
Public methodClone
Creates a deep copy of this regression calculator instance.
Public methodFactor(DoubleMatrix)
Factors a given matrix so that it may be used to solve least squares problems.
Public methodFactor(DoubleMatrix, Double)
Factors a given matrix so that it may be used to solve least squares problems. The specified tolerance is used in computing the numerical rank of the matrix.
Public methodFactor(DoubleMatrix, Double, Boolean)
Factors a given matrix so that it may be used to solve least squares problems. The specified tolerance is used in computing the numerical rank of the matrix.
Public methodResidualNormSqr
Computes the 2-norm squared of the residual vector.
Public methodResidualVector
Computes and returns the residual vector.
Public methodSolve
Computes the solution to the least squares problem Ax = b.
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Remarks
Class QRRegressionCalculation finds the minimal norm solution to the overdetermined linear system:
Ax = b
That is, this class finds the vector x that minimizes the 2-norm of the residual vector Ax - b. Prerequisites on the matrix A are that it has more rows than columns, and is of full rank.
See Also