Towards A Backward Perturbation Analysis For Data Least Squares Problems

Abstract

Given an approximate solution to a data least squares (DLS) problem, we would like to know its minimal backward error. Here we derive formulas for what we call an “extended” minimal backward error, which is at worst a lower bound on the minimal backward error. When the given approximate solution is a good enough approximation to the exact solution of the… (More)
DOI: 10.1137/060668626

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Cite this paper

@article{Chang2008TowardsAB, title={Towards A Backward Perturbation Analysis For Data Least Squares Problems}, author={Xiao-Wen Chang and Gene H. Golub and Christopher C. Paige}, journal={SIAM J. Matrix Analysis Applications}, year={2008}, volume={30}, pages={1281-1301} }