Package | Description |
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org.ojalgo.matrix.decomposition |
Modifier and Type | Interface and Description |
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interface |
Cholesky<N extends Number>
Cholesky: [A] = [L][L]H (or [R]H[R])
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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).
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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] ( [PL][L][D][U][PU] )
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interface |
LU<N extends Number>
LU: [A] = [L][U]
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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.
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static interface |
MatrixDecomposition.Values<N extends Number>
Eigenvalue and Singular Value decompositions can calculate the "values" only.
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interface |
QR<N extends Number>
QR: [A] = [Q][R] Decomposes [this] into [Q] and [R] where:
[Q] is an orthogonal matrix (orthonormal columns).
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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.
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Modifier and Type | Class and Description |
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class |
HermitianEvD<N extends Number>
Eigenvalues and eigenvectors of a real matrix.
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