Comments (3)
It is true that SVD exists for all matrices. It is also thinkable that our algorithm to compute it could fail with a NonconvergenceException, since the algorithm we use (which is quite standard) is iterative and relies on numerical convergence. However, for the values you quote, I am unable to reproduce the described behavior. The following code executes for me without any exception, and produces a working SVD:
RectangularMatrix M = new RectangularMatrix(new double[,] {
{ 44.6667, -392.0000, -66.0000 },
{ -392.0000, 3488.0000, 504.0001 },
{ -66.0000, 504.0001, 216.0001 }
});
//M = M.Transpose;
SingularValueDecomposition S = M.SingularValueDecomposition();
Note that I also tried with the transpose, in case we disagreed about column vs row ordering.
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If you can send me explicit code that fails, I would be happy to debug the behavior.
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Hi dcwuser, thanks for your reply. Unfortunately, it is a bit ago that I encountered the situation and, afaik, i implemented SVD from some different library at that place which behaved more robustly with these data. I cannot reproduce all of it right now, but I will try to when I am back in office.
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