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CORegressionCalculation Class

Class CORegressionCalculation computes linear regression parameters by the method of least squares using a complete orthogonal decomposition.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreCORegressionCalculation

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.3
Syntax
[SerializableAttribute]
public class CORegressionCalculation : IRegressionCalculation, 
	ICloneable

The CORegressionCalculation type exposes the following members.

Constructors
  NameDescription
Public methodCORegressionCalculation
Constructs a CORegressionCalculation instance with a default tolerance of zero.
Public methodCORegressionCalculation(Double)
Constructs a CORegressionCalculation instance with a given tolerance.
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Properties
  NameDescription
Public propertyRank
Gets the rank of the regression matrix.
Public propertyRankAvailable
Gets a boolean value indicating whether or not the rank for the regression matrix is available.
Public propertyTolerance
Gets and sets the tolerance used in computing the effective rank of the regression matrix.
Public propertyXTXInv
Gets the inverse of the matrix formed by taking the product of the regression matrix with its transpose, if available.
Public propertyXTXInvAvailable
Gets a boolean indicating whether or not the matrix formed by taking the inverse of the product of the transpose of the regression matrix with itself is avaialble as part of the decomposition.
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Methods
  NameDescription
Public methodCalculateParameters(DoubleMatrix, DoubleVector)
Calculates the parameters for a regression using a complete orthogonal decomposition of the regression matrix to solve the least squares problem.
Public methodCalculateParameters(DoubleMatrix, DoubleVector, Boolean)
Calculates the parameters for a regression using a complete orthogonal decomposition of the regression matrix to solve the least squares problem.
Public methodClone
Creates a deep copy of this CORegressionCalculation.
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Remarks
Class CORegressionCalculation 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.
See Also