Stats.NearestCorrelationMatrix Method

Definition

Namespace: Numerics.NET.Statistics
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4

Overload List

NearestCorrelationMatrix(SymmetricMatrix<Double>)	Returns a positive semi-definite matrix close to a matrix.
NearestCorrelationMatrix(SymmetricMatrix<Double>, NearestCorrelationMatrixAlgorithm)	Returns a positive semi-definite matrix close to a matrix.
NearestCorrelationMatrix(SymmetricMatrix<Double>, NearestCorrelationMatrixAlgorithm, Double, Int32, Double)	Returns a positive semi-definite matrix close to a matrix.

NearestCorrelationMatrix(SymmetricMatrix<Double>)

Returns a positive semi-definite matrix close to a matrix.

public static SymmetricMatrix<double> NearestCorrelationMatrix(
	SymmetricMatrix<double> matrix
)

Visual Basic

Public Shared Function NearestCorrelationMatrix ( 
	matrix As SymmetricMatrix(Of Double)
) As SymmetricMatrix(Of Double)

C++/CLI

public:
static SymmetricMatrix<double>^ NearestCorrelationMatrix(
	SymmetricMatrix<double>^ matrix
)

static member NearestCorrelationMatrix : 
        matrix : SymmetricMatrix<float> -> SymmetricMatrix<float>

Parameters

matrix SymmetricMatrix<Double>: A symmetric matrix.

Return Value

SymmetricMatrix<Double>
A symmetric matrix that is positive semi-definite. If matrix itself is positive semi-definite, it is returned unchanged.

Remarks

This method uses the alternating projections method of Nigham.

NearestCorrelationMatrix(SymmetricMatrix<Double>, NearestCorrelationMatrixAlgorithm)

Returns a positive semi-definite matrix close to a matrix.

public static SymmetricMatrix<double> NearestCorrelationMatrix(
	SymmetricMatrix<double> matrix,
	NearestCorrelationMatrixAlgorithm algorithm
)

Visual Basic

Public Shared Function NearestCorrelationMatrix ( 
	matrix As SymmetricMatrix(Of Double),
	algorithm As NearestCorrelationMatrixAlgorithm
) As SymmetricMatrix(Of Double)

C++/CLI

public:
static SymmetricMatrix<double>^ NearestCorrelationMatrix(
	SymmetricMatrix<double>^ matrix, 
	NearestCorrelationMatrixAlgorithm algorithm
)

static member NearestCorrelationMatrix : 
        matrix : SymmetricMatrix<float> * 
        algorithm : NearestCorrelationMatrixAlgorithm -> SymmetricMatrix<float>

Parameters

matrix SymmetricMatrix<Double>: A symmetric matrix.
algorithm NearestCorrelationMatrixAlgorithm: Specifies the algorithm used to compute the matrix.

Return Value

SymmetricMatrix<Double>
A symmetric matrix that is positive semi-definite. If matrix itself is positive semi-definite, it is returned unchanged.

Remarks

This method uses a method by Rebonato and Jäckel (scaled projection) or the alternating projections method of Nigham.

NearestCorrelationMatrix(SymmetricMatrix<Double>, NearestCorrelationMatrixAlgorithm, Double, Int32, Double)

Returns a positive semi-definite matrix close to a matrix.

public static SymmetricMatrix<double> NearestCorrelationMatrix(
	SymmetricMatrix<double> matrix,
	NearestCorrelationMatrixAlgorithm algorithm = NearestCorrelationMatrixAlgorithm.AlternatingProjections,
	double tolerance = 1E-10,
	int maxIterations = 100,
	double minEigenvalue = 0
)

Visual Basic

Public Shared Function NearestCorrelationMatrix ( 
	matrix As SymmetricMatrix(Of Double),
	Optional algorithm As NearestCorrelationMatrixAlgorithm = NearestCorrelationMatrixAlgorithm.AlternatingProjections,
	Optional tolerance As Double = 1E-10,
	Optional maxIterations As Integer = 100,
	Optional minEigenvalue As Double = 0
) As SymmetricMatrix(Of Double)

C++/CLI

public:
static SymmetricMatrix<double>^ NearestCorrelationMatrix(
	SymmetricMatrix<double>^ matrix, 
	NearestCorrelationMatrixAlgorithm algorithm = NearestCorrelationMatrixAlgorithm::AlternatingProjections, 
	double tolerance = 1E-10, 
	int maxIterations = 100, 
	double minEigenvalue = 0
)

static member NearestCorrelationMatrix : 
        matrix : SymmetricMatrix<float> * 
        ?algorithm : NearestCorrelationMatrixAlgorithm * 
        ?tolerance : float * 
        ?maxIterations : int * 
        ?minEigenvalue : float 
(* Defaults:
        let _algorithm = defaultArg algorithm NearestCorrelationMatrixAlgorithm.AlternatingProjections
        let _tolerance = defaultArg tolerance 1E-10
        let _maxIterations = defaultArg maxIterations 100
        let _minEigenvalue = defaultArg minEigenvalue 0
*)
-> SymmetricMatrix<float>

Parameters

matrix SymmetricMatrix<Double>: A symmetric matrix.
algorithm NearestCorrelationMatrixAlgorithm (Optional): Specifies the algorithm used to compute the matrix.
tolerance Double (Optional): The relative tolerance used to test for convergence.
maxIterations Int32 (Optional): The maximum number of iterations to perform.
minEigenvalue Double (Optional): Optional. A minimum for the smallest eigenvalue of the returned matrix. The default value is zero.

Return Value

SymmetricMatrix<Double>
A symmetric matrix that is positive semi-definite. If matrix itself is positive semi-definite, it is returned unchanged.

Remarks

This method uses a method by Rebonato and Jäckel (scaled projection) or the alternating projections method of Nigham.

Rebonato and Jäckel's method uses a direct approximation. The Nigham algorithm computes the matrix nearest to matrix in the sense that the sum of the squares of the differences between corresponding elements is minimized.

Exceptions

ArgumentOutOfRangeException

tolerance is less than zero.

-or-

maxIterations is less than one.

-or-

minEigenvalue is less than zero.

Stats.NearestCorrelationMatrix Method

Definition

Overload List

NearestCorrelationMatrix(SymmetricMatrix<Double>)

Parameters

Return Value

Remarks

NearestCorrelationMatrix(SymmetricMatrix<Double>, NearestCorrelationMatrixAlgorithm)

Parameters

Return Value

Remarks

NearestCorrelationMatrix(SymmetricMatrix<Double>, NearestCorrelationMatrixAlgorithm, Double, Int32, Double)

Parameters

Return Value

Remarks

Exceptions

See Also

Reference