Visual Error Criteria for Qualitative Smoothing

Marron, JS.;Tsybakov, AB.
(1995) Journal of the American Statistical Association — Vol. 90, n° 430, p. 499-507 (1995)

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  • Marron, JS.
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  • Tsybakov, AB.
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Abstract
An important gap, between the classical mathematical theory and the practice and implementation of nonparametric curve estimation, is due to the fact that the usual norms on function spaces measure something different from what the eye can see visually in a graphical presentation. Mathematical error criteria that more closely follow ''visual impression'' are developed and analyzed from both graphical and mathematical viewpoints. Examples from wavelet regression and kernel density estimation are considered.
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Marron, JS., & Tsybakov, AB. (1995). Visual Error Criteria for Qualitative Smoothing. Journal of the American Statistical Association, 90(430), 499-507. https://doi.org/10.2307/2291060 (Original work published 1995)