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
syntax is
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
known fix?
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
This message is intended solely for the designated recipient(s). It may contain confidential or proprietary information and may be subject to confidentiality protections. If you are not a designated recipient, you may not review, copy, or distribute this message. If you receive this in error, please notify the sender by reply e-mail and delete this message.
Arrowstreet Capital, L.P. is an Equal Opportunity Employer.
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
