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st: possible bug in the singular value decomposition (matrix svd)
Hi everybody. I'm running constrained regressions with nearly singular
covariate matricies. I use the singular value decomposition to produce
generalized inverses which are numerically stable. I think that I have
found a problem with the matrix svd command in STATA 8. The command
matrix svd U M V = A
The resulting matricies should satisfy the equality A = U*diag(M)*V'.
For a particular matrix, I find that the equality fails beyond the usual
errors due to numerical imprecision. When I feed exactly the same matrix
into the mata "fullsvd" command in STATA 9, the problem is resolved.
However, for a number of reasons, we need to keep using STATA 8 here.
So: is there a known bug in the matrix svd command? If so, is there a
Thanks a lot,
Sam Thompson, Arrowstreet Capital, LLP
If anyone wants, I can send the matrix along. It's not too big - 62 x 60
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