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- W2087156936 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." @default.
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- W2087156936 date "2003-08-19" @default.
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- W2087156936 title "Perturbation analysis for circles, spheres, and generalized hyperspheres fitted to data by geometric total least-squares" @default.
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- W2087156936 doi "https://doi.org/10.1090/s0025-5718-03-01613-2" @default.
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