Linear |
Computes the minimum-norm solution to a real linear least squares problem: minimize 2-norm(|| A*X - B||)
involving an M-by-N matrix A. The problem can be solved using: 1) A QR or LQ
factorization, 2) Complete orthogonal factorization, 3) Using singular value decomposition (SVD).
Inheritance HierarchyNamespace: DotNumerics.LinearAlgebra
Assembly: DWSIM.MathOps.DotNumerics (in DWSIM.MathOps.DotNumerics.dll) Version: 1.0.0.0 (1.0.0.0)
SyntaxThe LinearLeastSquares type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | LinearLeastSquares | Initializes a new instance of the LinearLeastSquares class. |
Methods| Name | Description | |
|---|---|---|
 | CalculateLIWORK | Calcula LIWORK para ser usado en IWORK. Este programa se encuentra en el foro de preguntas de Lapack |
| COFSolve(Matrix, Matrix) | Computes the minimum-norm solution to a real linear least squares problem: minimize 2-norm(|| A*X - B||) using a complete orthogonal factorization of A. The matrix A can be rank-deficient. |
| COFSolve(Matrix, Matrix, Double) | Computes the minimum-norm solution to a real linear least squares problem: minimize 2-norm(|| A*X - B||) using a complete orthogonal factorization of A. The matrix A can be rank-deficient. |
| QRorLQSolve | Solves overdetermined or underdetermined real linear systems involving an M-by-N matrix A, using a QR or LQ factorization of A. It is assumed that A has full rank. |
| SVDdcSolve(Matrix, Matrix) | Computes the minimum-norm solution to a real linear least squares problem: minimize 2-norm(|| A*X - B||) using the singular value decomposition (SVD) of A. The matrix A can be rank-deficient. |
| SVDdcSolve(Matrix, Matrix, Double) | Computes the minimum-norm solution to a real linear least squares problem: minimize 2-norm(|| A*X - B||) using the singular value decomposition (SVD) of A. The matrix A can be rank-deficient. |
Fields
Extension Methods| Name | Description | |
|---|---|---|
 | GetEnumNames | (Defined by General) |
| IsValidDouble | (Defined by General) |
See Also