Abstract
The method of normal equations, the Peters–Wilkinson algorithm and an algorithm based on Givens rotations for solving large sparse linear least squares problems are discussed and compared. Numerical experiments show that the method of normal equations should be considered when the observation matrix is sparse and well conditioned. For ill-conditioned problems, the algorithm based on Givens rotations is preferable.
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