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Add doc page on computing Least Squares.

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Jitse Niesen
2014-01-18 01:16:17 +00:00
parent a58325ac2f
commit aa0db35185
5 changed files with 86 additions and 5 deletions
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doc/TutorialLinearAlgebra.dox
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@@ -167,8 +167,8 @@ Here is an example:
\section TutorialLinAlgLeastsquares Least squares solving
The best way to do least squares solving is with a SVD decomposition. Eigen provides one as the JacobiSVD class, and its solve()
is doing least-squares solving.
The most accurate method to do least squares solving is with a SVD decomposition. Eigen provides one
as the JacobiSVD class, and its solve() is doing least-squares solving.
Here is an example:
<table class="example">
@@ -179,9 +179,10 @@ Here is an example:
</tr>
</table>
Another way, potentially faster but less reliable, is to use a LDLT decomposition
of the normal matrix. In any case, just read any reference text on least squares, and it will be very easy for you
to implement any linear least squares computation on top of Eigen.
Another methods, potentially faster but less reliable, are to use a Cholesky decomposition of the
normal matrix or a QR decomposition. Our page on \link LeastSquares least squares solving \endlink
has more details.
\section TutorialLinAlgSeparateComputation Separating the computation from the construction