Uses of Interface
org.ojalgo.matrix.decomposition.MatrixDecomposition.Ordered

Packages that use MatrixDecomposition.Ordered

Package	Description
org.ojalgo.matrix.decomposition

Uses of MatrixDecomposition.Ordered in org.ojalgo.matrix.decomposition

Subinterfaces of MatrixDecomposition.Ordered in org.ojalgo.matrix.decomposition

Modifier and Type	Interface and Description
interface	Cholesky<N extends Number> Cholesky: [A] = [L][L]H (or [R]H[R])
interface	Eigenvalue<N extends Number> [A] = [V][D][V]-1 ([A][V] = [V][D]) [A] = any square matrix. [V] = contains the eigenvectors as columns. [D] = a diagonal matrix with the eigenvalues on the diagonal (possibly in blocks).
interface	LDL<N extends Number> LDL: [A] = [L][D][L]H (or [R]H[D][R])
interface	LDU<N extends Number> LDU: [A] = [L][D][U] ( [P1][L][D][U][P2] )
interface	LU<N extends Number> LU: [A] = [L][U]
static interface	MatrixDecomposition.RankRevealing<N extends Number> A rank-revealing matrix decomposition of a matrix [A] is a decomposition that is, or can be transformed to be, on the form [A]=[X][D][Y]T where: [X] and [Y] are square and well conditioned. [D] is diagonal with nonnegative and non-increasing values on the diagonal.
static interface	MatrixDecomposition.Values<N extends Number> Eigenvalue and Singular Value decompositions can calculate the "values" only, and the resulting matrices and arrays can have their elements sorted (descending) or not.
interface	QR<N extends Number> QR: [A] = [Q][R] Decomposes [this] into [Q] and [R] where: [Q] is an orthogonal matrix (orthonormal columns).
interface	SingularValue<N extends Number> Singular Value: [A] = [Q1][D][Q2]T Decomposes [this] into [Q1], [D] and [Q2] where: [Q1] is an orthogonal matrix.

Classes in org.ojalgo.matrix.decomposition that implement MatrixDecomposition.Ordered

Modifier and Type	Class and Description
class	HermitianEvD<N extends Number> Eigenvalues and eigenvectors of a real matrix.