On Tue, Jun 29, 2010 at 6:03 PM, David Goldsmith <[email protected]> wrote: > On Tue, Jun 29, 2010 at 3:56 PM, <[email protected]> wrote: >> >> On Tue, Jun 29, 2010 at 6:37 PM, David Goldsmith >> <[email protected]> wrote: >> > ...concerns the behavior of numpy.random.multivariate_normal; if that's >> > of >> > interest to you, I urge you to take a look at the comments (esp. mine >> > :-) ); >> > otherwise, please ignore the noise. Thanks! >> >> You should add the link to the ticket, so it's faster for everyone to >> check what you are talking about. >> >> Josef > > Ooops! Yes I should; here it is: > > http://projects.scipy.org/numpy/ticket/1223 > Sorry, and thanks, Josef. > > DG > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > As I recall, there is no requirement for the variance/covariance of the normal distribution to be positive definite. >From http://en.wikipedia.org/wiki/Multivariate_normal_distribution "The covariance matrix is allowed to be singular (in which case the corresponding distribution has no density)."
So you must be able to draw random numbers from such a distribution. Obviously what those numbers really mean is another matter (I presume the dependent variables should be a linear function of the independent variables) but the user *must* know since they entered it. Since the function works the docstring Notes comment must be wrong. Imposing any restriction means that this is no longer a multivariate normal random number generator. If anything, you can only raise a warning about possible non-positive definiteness but even that will vary depending how it is measured and on the precision being used. Bruce _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
