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https://issues.apache.org/jira/browse/MATH-541?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Luc Maisonobe resolved MATH-541.
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Resolution: Fixed
fixed in subversion repository as of r1096496
> add a "rectangular" Cholesky-like decomposition
> -----------------------------------------------
>
> Key: MATH-541
> URL: https://issues.apache.org/jira/browse/MATH-541
> Project: Commons Math
> Issue Type: Improvement
> Affects Versions: 2.2
> Reporter: Luc Maisonobe
> Assignee: Luc Maisonobe
> Priority: Minor
> Fix For: 3.0
>
>
> The CorrelatedRandomVectorGenerator class uses a kind of rectangular
> Cholesky-like transform M = B.Bt where B is a rectangular matrix. The
> difference with respect to a regular Cholesky decomposition is that
> rows/columns may be permuted (hence the rectangular shape instead of the
> traditional triangular shape) and there is a threshold to ignore small
> diagonal elements. This is used for example to generate correlated random
> n-dimensions vectors in a p-dimension subspace (p < n). In other words, it
> allows generating random vectors from a covariance matrix that is only
> positive semidefinite, and not positive definite.
> It would be nice to have this decomposition available as a stand-alone class
> outside of the CorrelatedRandomVectorGenerator.
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