On orthogonal polynomials transformed by the QR algorithm
Journal of Computational and Applied Mathematics - Orthogonal polynomials and numerical methods
Some functions that generalize the Krall-Laguerre polynomials
Journal of Computational and Applied Mathematics
Accuracy and Stability of Numerical Algorithms
Accuracy and Stability of Numerical Algorithms
Error analysis of the mdLVs algorithm for computing bidiagonal singular values
Numerical Algorithms
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A monic Jacobi matrix is a tridiagonal matrix which contains the parameters of the three-term recurrence relation satisfied by the sequence of monic polynomials orthogonal with respect to a measure. The basic Christoffel transformation with shift @a transforms the monic Jacobi matrix associated with a measure d@m into the monic Jacobi matrix associated with (x-@a)d@m. This transformation is known for its numerous applications to quantum mechanics, integrable systems, and other areas of mathematics and mathematical physics. From a numerical point of view, the Christoffel transformation is essentially computed by performing one step of the LR algorithm with shift, but this algorithm is not stable. We propose a more accurate algorithm, estimate its forward errors, and prove that it is forward stable, i.e., that the obtained forward errors are of similar magnitude to those produced by a backward stable algorithm. This means that the magnitude of the errors is the best one can expect, because it reflects the sensitivity of the problem to perturbations in the input data.