Hello, I am working on submitting code for multivariate normal distributions, including sampling and unit tests (issue Math-815). It is my first submission, and it has had some issues with style and other guidelines. Gilles has given me some useful feedback about several pieces, but I thought I would also ask a question this list.
I need to have a unit test pass deterministically even though the sampling algorithm is inherently stochastic. I assumed that resetting the seed before sampling would be sufficient to test a few values to within a specified tolerance. It has worked so far for me. Gilles suggested, though, that I use the testSampling method in RealDistributionAbstractTest.java as a model. But it uses a statistical test (Chi-Squared) in addition to resetting the seed. Aside from the added difficulty of hypothesis testing in more dimensions, is it actually necessary? Wouldn't resetting the seed give you the same values each time when you sample in the unit test? Doesn't that make it essentially a deterministic test, eliminating the need for a hypothesis test of the samples? Thanks, Jared Email Disclaimer: www.stjude.org/emaildisclaimer Consultation Disclaimer: www.stjude.org/consultationdisclaimer --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
