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Diffstat (limited to 'doc/LeastSquares.dox')
| -rw-r--r-- | doc/LeastSquares.dox | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/LeastSquares.dox b/doc/LeastSquares.dox index e2191a22f..24dfe4b4f 100644 --- a/doc/LeastSquares.dox +++ b/doc/LeastSquares.dox @@ -16,7 +16,7 @@ equations is the fastest but least accurate, and the QR decomposition is in betw \section LeastSquaresSVD Using the SVD decomposition -The \link JacobiSVD::solve() solve() \endlink method in the JacobiSVD class can be directly used to +The \link BDCSVD::solve() solve() \endlink method in the BDCSVD class can be directly used to solve linear squares systems. It is not enough to compute only the singular values (the default for this class); you also need the singular vectors but the thin SVD decomposition suffices for computing least squares solutions: |