On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig <[email protected]>wrote:
> Le 16/02/2012 16:20, [email protected] a écrit : > > I don't see any way to fix multivariate_normal for this case, except >> for dropping svd or for random perturbing a covariance matrix with >> multiplicity of singular values. >> > Hi, > I just made a quick search in what R guys are doing. It happens there are > several codes > (http://cran.r-project.org/**web/views/Multivariate.html<http://cran.r-project.org/web/views/Multivariate.html>). > For instance, mvtnorm ( > http://cran.r-project.org/**web/packages/mvtnorm/index.**html<http://cran.r-project.org/web/packages/mvtnorm/index.html>). > I've attached the related function from the source code of this package. > > Interestingly enough, it seems they provide 3 different methods (svd, > eigen values, and Cholesky). > I don't have the time now to dive in the assessments of pros and cons of > those three. Maybe one works for our problem, but I didn't check yet. > > Pierre > > For some alternatives to numpy's multivariate_normal, see http://www.scipy.org/Cookbook/CorrelatedRandomSamples. Both versions (Cholesky and eigh) are just a couple lines of code. Warren
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