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Perturbation analysis for circles, spheres, and generalized hyperspheres fitted to data by geometric total least-squares


Author: Yves Nievergelt
Journal: Math. Comp. 73 (2004), 169-180
MSC (2000): Primary 65D10, 51M16
DOI: https://doi.org/10.1090/S0025-5718-03-01613-2
Published electronically: August 19, 2003
MathSciNet review: 2034115
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Abstract | References | Similar Articles | Additional Information

Abstract: A continuous extension of the objective function to a projective space guarantees that for each data set there exists at least one hyperplane or hypersphere minimizing the average squared distance to the data. For data sufficiently close to a hypersphere, as the collinearity of the data increases, so does the sensitivity of the fitted hypersphere to perturbations of the data.


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Additional Information

Yves Nievergelt
Affiliation: Department of Mathematics, Eastern Washington University, 216 Kingston Hall, Cheney, Washington 99004-2418
Email: ynievergelt@ewu.edu

DOI: https://doi.org/10.1090/S0025-5718-03-01613-2
Keywords: Fitting, geometric, circles, spheres, total least-squares
Received by editor(s): January 3, 2001
Received by editor(s) in revised form: April 24, 2002
Published electronically: August 19, 2003
Additional Notes: Work done at the University of Washington during a leave from Eastern Washington University.
Article copyright: © Copyright 2003 American Mathematical Society

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