﻿DoubleSVDLeastSq Class   # DoubleSVDLeastSq Class

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

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

The DoubleSVDLeastSq type exposes the following members. Constructors
NameDescription DoubleSVDLeastSq
Constructs a DoubleSVDLeastSq instance with all sizes zero. DoubleSVDLeastSq(DoubleMatrix)
Constructs a DoubleSVDLeastSq instance from the given matrix. DoubleSVDLeastSq(DoubleMatrix, Double)
Constructs a DoubleSVDLeastSq instance from the given matrix. The specified tolerance is used in computing the numerical rank of the matrix.
Top Properties
NameDescription Cols
Gets the number of columns in the matrix. Fail
Gets the status of the singular value decomposition. IsGood
Gets a boolean value that is true if the singular value decomposition may be used to solve least squares problems; otherwise false. Rank
Gets the numerical rank of the matrix. Rows
Gets the number of rows in the matrix.
Top Methods
NameDescription Clone
Creates a deep copy of this least squares instance. Factor(DoubleMatrix)
Factors a given matrix so that it may be used to solve least squares problems. Factor(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. OnSerializing
processing following deserialization ResidualNormSqr
Computes the 2-norm squared of the residual vector. ResidualVector
Computes and returns the residual vector. Solve
Computes the solution to the least squares problem Ax = b.
Top Remarks
Use class DoubleSVDLeastSq 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