Backward error and condition number analysis for the indefinite linear least squares problem

Optimal backward perturbation bounds for the linear least squares problem

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...

Estimation of Backward Perturbation Bounds for Linear Least Squares Problem

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...

A Partial Condition Number for Linear Least Squares Problems

Abstract. We consider here the linear least squares problem miny∈Rn ‖Ay− b‖2, where b ∈ Rm and A ∈ Rm×n is a matrix of full column rank n, and we denote x its solution. We assume that both A and b can be perturbed and that these perturbations are measured using the Frobenius or the spectral norm for A and the Euclidean norm for b. In this paper, we are concerned with the condition number of a l...

Solving the Indefinite Least Squares Problem

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On the condition number of the total least squares problem