Large scale least squares scattered data fitting

DOI10.1016/S0168-9274(02)00147-2zbMath1013.65010OpenAlexW2017310586MaRDI QIDQ1861983

Yanyan Li

Publication date: 10 March 2003

Published in: Applied Numerical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0168-9274(02)00147-2

zbMATH Keywords

singular value decompositionleast squaresLanczos algorithmregularization methodsscattered data fittingtensor products of B-splines

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Numerical solutions to overdetermined systems, pseudoinverses (65F20)

Related Items (4)

Constructing B-spline solids from tetrahedral meshes for isogeometric analysis ⋮ Least squares collocation solution of elliptic problems in general regions ⋮ Variable projections neural network training ⋮ The convergence of least-squares progressive iterative approximation for singular least-squares fitting system

Uses Software

• LSQR
• CRAIG

Cites Work

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• The triangle method for finding the corner of the L-curve
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• Estimation of the \(L\)-curve via Lanczos bidiagonalization
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• An Improved Algorithm for Computing the Singular Value Decomposition
• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Iterative SVD-Based Methods for Ill-Posed Problems
• Least squares scattered data fitting by truncated SVDs

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