Click or drag to resize

FloatSVDLeastSq Class

Class FloatSVDLeastSq solves least squares problems by using a singular value decomposition.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreFloatSVDLeastSq

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

The FloatSVDLeastSq type exposes the following members.

Constructors
  NameDescription
Public methodFloatSVDLeastSq
Constructs a FloatSVDLeastSq instance with all sizes zero.
Public methodFloatSVDLeastSq(FloatMatrix)
Constructs a FloatSVDLeastSq instance from the given matrix.
Public methodFloatSVDLeastSq(FloatMatrix, Single)
Constructs a FloatSVDLeastSq instance from the given matrix. The specified tolerance is used in computing the numerical rank of the matrix.
Top
Properties
  NameDescription
Public propertyCols
Gets the number of columns in the matrix.
Public propertyFail
Gets the status of the singular value decomposition.
Public propertyIsGood
Gets a boolean value that is true if the singular value decomposition may be used to solve least squares problems; otherwise false.
Public propertyRank
Gets the numerical rank of the matrix.
Public propertyRows
Gets the number of rows in the matrix.
Top
Methods
  NameDescription
Public methodClone
Creates a deep copy of this least squares instance.
Public methodFactor(FloatMatrix)
Factors a given matrix so that it may be used to solve least squares problems.
Public methodFactor(FloatMatrix, Single)
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 methodOnSerializing
processing following deserialization
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.
Top
Remarks
Use class FloatSVDLeastSq to find the minimal norm solution to the overdetermined linear system:
Ax = b
That is, find 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