MQL5 リファレンス行列とベクトルのメソッドOpenBLASSingular Value DecompositionSingularValueDecompositionBidiagDC

SingularValueDecompositionBidiagDC

Singular Value Decomposition, divide-and-conquer algorithm for bidiagonal matrices (LAPACK function BDSDC).

Computing for type matrix<double>

bool matrix::SingularValueDecompositionBidiagDC(
ENUM_SVDBIDIAG_Z jobz, // how to compute singular vectors
vector& S, // vector of computed singular values
matrix& U, // U matrix of computed left vectors
matrix& VT // VT transposed matrix of right vectors
);

Computing for type matrix<float>

bool matrixf::SingularValueDecompositionBidiagDC(
ENUM_SVDBIDIAG_Z jobz, // how to compute singular vectors
vectorf& S, // vector of computed singular values
matrixf& U, // U matrix of computed left vectors
matrixf& VT // VT transposed matrix of right vectors
);

Parameters

jobz

[in] ENUM_SVDBIDIAG_Z enumeration value that determines how the singular vectors should be computed.

[out] Vector of singular values.

[out] Matrix of left singular vectors.

[out] Transposed matrix of right singular vectors.

Return Value

Return true if successful, otherwise false in case of an error.

Note

Computation depends on the values of the jobz and range parameters.

A bidiagonal matrix is a square matrix with non-zero main diagonal and one of the sub-diagonals.

Upper bidiagonal matrix

[[x, x, 0, 0, 0],
[0, x, x, 0, 0],
[0, 0, x, x, 0],
[0, 0, 0, x, x],
[0, 0, 0, 0, x]]

Lower bidiagonal matrix

[[x, 0, 0, 0, 0],
[x, x, 0, 0, 0],
[0, x, x, 0, 0],
[0, 0, x, x, 0],
[0, 0, 0, x, x]]

ENUM_SVDBIDIAG_Z

An enumeration defining how left singular vectors should be computed.

ID	Description
SVDJOBZ_V	Compute singular values and singular vectors.
SVDJOBZ_N	Compute singular values only.