Abstract
In sparse matrix applications it is often important to implement the Cholesky and LDL T factorization methods without pivoting in order to avoid excess fillin. We consider methods for detection of a nearly singular matrix by means of these factorizations without pivoting and demonstrate that a technique based on estimation of the smallest eigenvalue via inverse iteration will always reveal a nearly singular matrix.
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