Hi Phil,
Thanks for the answer, and I was talking about numerical stability.
On an other track, if the math group is interested, I can provide some classes for Multivariate Minimum Volume Ellipsoid outlier detection, Covariances, common matrix types as SSCP, covariance and correlation, multivariate euclidian and mahalanobis distances and maybe some other classes as model 2 regressions (RMA: Reduced Major Axis). Interested?
Kim
Phil Steitz wrote:
Kim van der Linde wrote:
Hi All,
I have a question. How stable are the matrix classes as implemented?
Cheers,
Kim
Hi Kim,
If your question is about the API, then the answer is that we are planning no changes prior to the imminent 1.0 release. If your question is about numerical stability, performance or correctness there are two things to say:
1) The javadoc describes the algorithms used to perform matrix operations. The algorithms are general purpose, so they will not always give the best results (or performance) for all matrices. For most practical problems, the implementations should work fine. Have a look at the docs and consult a numerical linear algebra text (or a numerical analyst) or ask more specific questions here if you want to know about individual operations. Eventually, we will provide support for a wider variety of algorithms. For 1.0, what you see now is what you get.
2) Our confidence in implementation correctness is based pretty much entirely on the unit tests at this point. This is new code, not yet released. We are in the process of cutting a release candidate including these classes. User feedback and/or additional test cases will be greatly appreciated.
Phil
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