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A general formulation of reweighted least squares fitting
Mathematics and Computers in Simulation, Volume: 225, Pages: 52 - 65
Swansea University Author: Nelly Villamizar
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DOI (Published version): 10.1016/j.matcom.2024.04.029
Abstract
We present a generalized formulation for reweighted least squares approximations. The goal of this article is twofold: firstly, to prove that the solution of such problem can be expressed as a convex combination of certain interpolants when the solution is sought in any finite-dimensional vector spa...
Published in: | Mathematics and Computers in Simulation |
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ISSN: | 0378-4754 |
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Elsevier BV
2024
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URI: | https://cronfa.swan.ac.uk/Record/cronfa66448 |
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2024-09-19T10:46:12.2784342 v2 66448 2024-05-16 A general formulation of reweighted least squares fitting 41572bcee47da6ba274ecd1828fbfef4 0000-0002-8741-7225 Nelly Villamizar Nelly Villamizar true false 2024-05-16 MACS We present a generalized formulation for reweighted least squares approximations. The goal of this article is twofold: firstly, to prove that the solution of such problem can be expressed as a convex combination of certain interpolants when the solution is sought in any finite-dimensional vector space; secondly, to provide a general strategy to iteratively update the weights according to the approximation error and apply it to the spline fitting problem. In the experiments, we provide numerical examples for the case of polynomials and splines spaces. Subsequently, we evaluate the performance of our fitting scheme for spline curve and surface approximation, including adaptive spline constructions. Journal Article Mathematics and Computers in Simulation 225 52 65 Elsevier BV 0378-4754 Weighted least squares; Interpolation; Fitting; Adaptive splines; Hierarchical splines 1 11 2024 2024-11-01 10.1016/j.matcom.2024.04.029 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Another institution paid the OA fee The authors would like to acknowledge the support provided by the 4th WiSh: Women in Shape Analysis Research Workshop. This collaboration began during the workshop, and we are deeply grateful for the opportunity to work with fellow researchers in the field. CGandSI are members of the INdAM group GNCS, whose support is gratefully acknowledged. LMK acknowledges support from Magdalene College, Cambridge (Nevile Research Fellowship). ELR work was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy EXC 2044–390685587, Mathematics Münster: DynamicsGeometry–Structure. FM was partially supported by the FWO grants (G0F5921N, G023721N), the KU Leuven iBOF/23/064 grant, and the UiT Aurora MASCOT project. NV was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) New Investigator Award EP/V012835/1 2024-09-19T10:46:12.2784342 2024-05-16T10:13:30.7044083 Faculty of Science and Engineering School of Mathematics and Computer Science - Mathematics Carlotta Giannelli 1 Sofia Imperatore 0009-0003-9116-9978 2 Lisa Maria Kreusser 0000-0002-1131-1125 3 Estefanía Loayza-Romero 0000-0001-7919-9259 4 Fatemeh Mohammadi 0000-0001-5187-0995 5 Nelly Villamizar 0000-0002-8741-7225 6 66448__31372__f4b66872f40a4b919b1ea0836e681ccd.pdf 66448.VoR.pdf 2024-09-19T10:43:42.7905867 Output 2359192 application/pdf Version of Record true © 2024 The Authors. This is an open access article under the CC BY license. true eng http://creativecommons.org/licenses/by/4.0/ |
title |
A general formulation of reweighted least squares fitting |
spellingShingle |
A general formulation of reweighted least squares fitting Nelly Villamizar |
title_short |
A general formulation of reweighted least squares fitting |
title_full |
A general formulation of reweighted least squares fitting |
title_fullStr |
A general formulation of reweighted least squares fitting |
title_full_unstemmed |
A general formulation of reweighted least squares fitting |
title_sort |
A general formulation of reweighted least squares fitting |
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41572bcee47da6ba274ecd1828fbfef4 |
author_id_fullname_str_mv |
41572bcee47da6ba274ecd1828fbfef4_***_Nelly Villamizar |
author |
Nelly Villamizar |
author2 |
Carlotta Giannelli Sofia Imperatore Lisa Maria Kreusser Estefanía Loayza-Romero Fatemeh Mohammadi Nelly Villamizar |
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Journal article |
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Mathematics and Computers in Simulation |
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Swansea University |
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0378-4754 |
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10.1016/j.matcom.2024.04.029 |
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Elsevier BV |
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description |
We present a generalized formulation for reweighted least squares approximations. The goal of this article is twofold: firstly, to prove that the solution of such problem can be expressed as a convex combination of certain interpolants when the solution is sought in any finite-dimensional vector space; secondly, to provide a general strategy to iteratively update the weights according to the approximation error and apply it to the spline fitting problem. In the experiments, we provide numerical examples for the case of polynomials and splines spaces. Subsequently, we evaluate the performance of our fitting scheme for spline curve and surface approximation, including adaptive spline constructions. |
published_date |
2024-11-01T08:35:52Z |
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1822118644050558976 |
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11.048388 |