﻿FloatComplexCholeskyLeastSq Class   # FloatComplexCholeskyLeastSq Class

Class FloatComplexCholeskyLeastSq solves least square problems by using the Cholesky factorization to solve the normal equations. Inheritance Hierarchy
SystemObject
CenterSpace.NMath.CoreFloatComplexCholeskyLeastSq

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

The FloatComplexCholeskyLeastSq type exposes the following members. Constructors
NameDescription FloatComplexCholeskyLeastSq
Constructs a FloatComplexCholeskyLeastSq instance with all sizes zero. FloatComplexCholeskyLeastSq(FloatComplexMatrix)
Constructs a FloatComplexCholeskyLeastSq instance from the given matrix.
Top Properties
NameDescription Cols
Gets the number of columns in the matrix. IsGood
Gets a boolean value which is true if the Cholesky factorization succeeded and may be used to solve least square problems; otherwise false. Rows
Gets the number of rows in the matrix.
Top Methods
NameDescription Clone
Creates a deep copy of this least squares instance. Factor
Factors a given matrix so that it may be used to solve least squares problems. 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
The normal equations for the least squares problem Ax = b are:
`A'Ax = A'b`
where A' denotes the transpose of the matrix A. If A has full rank, then A'A is symmetric positive definite (and, in fact, the converse is true). Thus, the Cholesky factorization may be used to solve the normal equations. Note this implies that this method will fail if A is rank deficiennt. See Also