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DigitalRuneQRDecompositionD Class
Computes the QR Decomposition of a matrix (double-precision).
Inheritance Hierarchy
SystemObject
  DigitalRune.Mathematics.AlgebraQRDecompositionD

Namespace: DigitalRune.Mathematics.Algebra
Assembly: DigitalRune.Mathematics (in DigitalRune.Mathematics.dll) Version: 1.14.0.0 (1.14.0.14427)
Syntax
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public class QRDecompositionD

The QRDecompositionD type exposes the following members.

Constructors
  NameDescription
Public methodQRDecompositionD
Creates the QR decomposition of the given matrix.
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Methods
  NameDescription
Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodSolveLinearEquations
Returns the least squares solution for the equation A * X = B.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Properties
  NameDescription
Public propertyH
Gets the matrix H with the Householder vectors. (This property returns the internal matrix, not a copy.)
Public propertyHasNumericallyFullRank
Gets a value indicating whether the matrix R has full rank (numerically).
Public propertyQ
Gets the orthogonal matrix Q. (This property returns the internal matrix, not a copy.)
Public propertyR
Gets the upper triangular matrix R. (This property returns the internal matrix, not a copy.)
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Remarks

For an m x n matrix A with m ≥ n the QR Decomposition computes an orthogonal matrix Q and a upper triangular matrix R so that A = Q * R.

The QR Decomposition always exists, even if the matrix does not have full rank.

Application: The primary use of QR Decomposition is in computing the least squares solution for non-square sets of linear equations. This will fail if the matrix does not have full rank.

See Also