Efficient recursive least squares solver for rank-deficient matrices

DOI10.1016/j.amc.2021.125996OpenAlexW3128026070MaRDI QIDQ2242621

Ruben Staub, Stephan N. Steinmann

Publication date: 10 November 2021

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2106.11594

zbMATH Keywords

generalized inverseMoore-Penrose pseudoinverserank-deficient linear systemsrecursive least-squares

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Uses Software

• LAPACK
• mctoolbox
• SciPy
• NumPy
• Python
• IPython

Cites Work

• Numerical aspects of computing the Moore-Penrose inverse of full column rank matrices
• A new method for computing Moore-Penrose inverse matrices
• Generalized inverses. Theory and applications.
• On the Moore-Penrose generalized inverse matrix
• Handbook series linear algebra. Linear least squares solutions by Householder transformations
• LAPACK Users' Guide
• Reorthogonalization and Stable Algorithms for Updating the Gram-Schmidt QR Factorization
• Accuracy and Stability of Numerical Algorithms
• A Method for Computing Least Squares Estimators that Keep Up with the Data
• Some Applications of the Pseudoinverse of a Matrix
• Numerical Linear Algebra
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