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From "Dimitri Pourbaix (JIRA)" <j...@apache.org>
Subject [jira] Created: (MATH-342) SVD crashes when applied to a strongly rectangular matrix (typical case of least-squares problem)
Date Sun, 21 Feb 2010 21:43:27 GMT
SVD crashes when applied to a strongly rectangular matrix (typical case of least-squares problem)
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                 Key: MATH-342
                 URL: https://issues.apache.org/jira/browse/MATH-342
             Project: Commons Math
          Issue Type: Bug
    Affects Versions: Nightly Builds
            Reporter: Dimitri Pourbaix
            Assignee: Dimitri Pourbaix


When SVD is applied to a strongly rectangular matrix (number of rows way larger than number
of columns, typical case of least-squares problem), finite precision arithmetics shows up:
 - in EigenDecompositionImpl.isSymmetric: a by-definition symmetric matrix returns false;
 - in EigenDecompositionImpl.findEigenVectors: too many iterations exception 

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