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Minor corrections in QR docs.
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Eigen/QR
4
Eigen/QR
@ -15,7 +15,9 @@
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*
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* This module provides various QR decompositions
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* This module also provides some MatrixBase methods, including:
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* - MatrixBase::qr(),
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* - MatrixBase::householderQr()
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* - MatrixBase::colPivHouseholderQr()
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* - MatrixBase::fullPivHouseholderQr()
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*
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* \code
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* #include <Eigen/QR>
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@ -33,13 +33,13 @@ struct traits<FullPivHouseholderQRMatrixQReturnType<MatrixType> >
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*
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* \param MatrixType the type of the matrix of which we are computing the QR decomposition
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*
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* This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b Q and \b R
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* This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b P', \b Q and \b R
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* such that
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* \f[
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* \mathbf{A} \, \mathbf{P} = \mathbf{Q} \, \mathbf{R}
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* \mathbf{P} \, \mathbf{A} \, \mathbf{P}' = \mathbf{Q} \, \mathbf{R}
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* \f]
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* by using Householder transformations. Here, \b P is a permutation matrix, \b Q a unitary matrix and \b R an
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* upper triangular matrix.
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* by using Householder transformations. Here, \b P and \b P' are permutation matrices, \b Q a unitary matrix
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* and \b R an upper triangular matrix.
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*
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* This decomposition performs a very prudent full pivoting in order to be rank-revealing and achieve optimal
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* numerical stability. The trade-off is that it is slower than HouseholderQR and ColPivHouseholderQR.
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