Least squares, singular values and matrix approximations

DOI10.21136/am.1968.103138zbMath0179.21403OpenAlexW2743834670MaRDI QIDQ5569883

Gene H. Golub

Publication date: 1968

Full work available at URL: https://eudml.org/doc/14515

zbMATH Keywords

numerical analysis

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Cites Work

• Unnamed Item
• Unnamed Item
• A generalized solution of the orthogonal Procrustes problem
• The orthogonal approximation of an oblique structure in factor analysis
• The QR Transformation A Unitary Analogue to the LR Transformation--Part 1
• SYMMETRIC GAUGE FUNCTIONS AND UNITARILY INVARIANT NORMS
• Calculating the Singular Values and Pseudo-Inverse of a Matrix
• Some Metric Inequalities in the Space of Matrices