I have another question, this time about the API.  The covariance matrix of a 
multivariate normal distribution is called sigma in a number of R libraries, 
but I am not sure it is called that everywhere.  I named the parameters and get 
methods for the covariance matrix things like "getSigma" but mentioned 
covariance matrix in the comments.  Do the developers here have a preference 
between getSigma and getCovarianceMatrix?  I can change the parameters 
accordingly.

Jared

-----Original Message-----
From: Becksfort, Jared
Sent: Tuesday, July 24, 2012 11:29 PM
To: Commons Developers List
Subject: [math] Unit Tests for Multivariate Distribution Sampling

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

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