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Least-Squares Fitting Algorithms of the NIST Algorithm Testing System
This report describes algorithms for fitting certain curves and surfaces to points in three dimensions. All fits are based on orthogonal distance regression. The algorithms were developed as reference software for the National Institute of Standards and Technology’s Algorithm Testing System, which h...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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[Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology
1998
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4890955/ https://www.ncbi.nlm.nih.gov/pubmed/28009376 http://dx.doi.org/10.6028/jres.103.043 |
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author | Shakarji, Craig M. |
author_facet | Shakarji, Craig M. |
author_sort | Shakarji, Craig M. |
collection | PubMed |
description | This report describes algorithms for fitting certain curves and surfaces to points in three dimensions. All fits are based on orthogonal distance regression. The algorithms were developed as reference software for the National Institute of Standards and Technology’s Algorithm Testing System, which has been used for 5 years by NIST and by members of the American Society of Mechanical Engineers’ B89.4.10 standards committee. The Algorithm Testing System itself is described only briefly; the main part of this paper covers the general linear algebra, numerical analysis, and optimization methods it employs. Most of the fitting routines rely on the Levenberg-Marquardt optimization routine. |
format | Online Article Text |
id | pubmed-4890955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 1998 |
publisher | [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology |
record_format | MEDLINE/PubMed |
spelling | pubmed-48909552016-12-22 Least-Squares Fitting Algorithms of the NIST Algorithm Testing System Shakarji, Craig M. J Res Natl Inst Stand Technol Article This report describes algorithms for fitting certain curves and surfaces to points in three dimensions. All fits are based on orthogonal distance regression. The algorithms were developed as reference software for the National Institute of Standards and Technology’s Algorithm Testing System, which has been used for 5 years by NIST and by members of the American Society of Mechanical Engineers’ B89.4.10 standards committee. The Algorithm Testing System itself is described only briefly; the main part of this paper covers the general linear algebra, numerical analysis, and optimization methods it employs. Most of the fitting routines rely on the Levenberg-Marquardt optimization routine. [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology 1998 1998-12-01 /pmc/articles/PMC4890955/ /pubmed/28009376 http://dx.doi.org/10.6028/jres.103.043 Text en https://creativecommons.org/publicdomain/zero/1.0/ The Journal of Research of the National Institute of Standards and Technology is a publication of the U.S. Government. The papers are in the public domain and are not subject to copyright in the United States. Articles from J Res may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. |
spellingShingle | Article Shakarji, Craig M. Least-Squares Fitting Algorithms of the NIST Algorithm Testing System |
title | Least-Squares Fitting Algorithms of the NIST Algorithm Testing System |
title_full | Least-Squares Fitting Algorithms of the NIST Algorithm Testing System |
title_fullStr | Least-Squares Fitting Algorithms of the NIST Algorithm Testing System |
title_full_unstemmed | Least-Squares Fitting Algorithms of the NIST Algorithm Testing System |
title_short | Least-Squares Fitting Algorithms of the NIST Algorithm Testing System |
title_sort | least-squares fitting algorithms of the nist algorithm testing system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4890955/ https://www.ncbi.nlm.nih.gov/pubmed/28009376 http://dx.doi.org/10.6028/jres.103.043 |
work_keys_str_mv | AT shakarjicraigm leastsquaresfittingalgorithmsofthenistalgorithmtestingsystem |