Incremental condition estimation for sparse matrices

Incremental condition estimation provides an estimate for the smallest singular value of a triangular matrix. In particular, it gives a running estimate of the smallest singular value of a triangular factor matrix as the factor is generated one column or row at a time. An incremental condition estimator for dense matrices was originally suggested by Bischof. In this paper this scheme is generalized to handle sparse triangular matrices, especially those that are factors of sparse matrices. Numerical experiments on a variety of matrices demonstrate the reliability of this scheme in estimating the smallest singular value. A partial description of its implementation in a sparse matrix factorization code further illustrates its practicality.