Backward Perturbation Bounds for Linear Least Squares Problems
نویسندگان
چکیده
منابع مشابه
Backward Perturbation Bounds for Linear Least Squares Problems
Recently, Higham and Wald en, Karlson, and Sun have provided formulas for computing the best backward perturbation bounds for the linear least squares problem. In this paper we provide several backward perturbation bounds that are easier to compute and optimal up to a factor less than 2. We also show that any least squares algorithm that is stable in the sense of Stewart is necessarily a backwa...
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Waldén, Karlson, and Sun found an elegant explicit expression of backward error for the linear least squares problem. However, it is difficult to compute this quantity as it involves the minimal singular value of certain matrix. In this paper we present a simple estimation to this bound which can be easily computed especially for large problems. Numerical results demonstrate the validity of the...
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Dedicated to William Kahan and Beresford Parlett on the occasion of their 60th birthdays Let A be an m n matrix, b be an m-vector, and x̃ be a purported solution to the problem of minimizing kb Axk2. We consider the following open problem: find the smallest perturbation E of A such that the vector x̃ exactly minimizes kb (A+E)xk2. This problem is completely solved whenE is measured in the Frobeni...
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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 DLS problem (which is the aim in practic...
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ژورنال
عنوان ژورنال: SIAM Journal on Matrix Analysis and Applications
سال: 1998
ISSN: 0895-4798,1095-7162
DOI: 10.1137/s0895479895296446