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Derivatives are a key nonparametric functional in wide-ranging applications where the rate of change of an unknown function is of interest.
The computation of fermi-dirac functions
McDougall, J. and Stoner, E. C. (1938) · 1938
Earlier work this paper cites.
Optimal global rates of convergence for nonparametric regression
Stone, C. J. (1982) · 1982
Earlier work this paper cites.
Spline smoothing in regression models and asymptotic efficiency in l2
Nussbaum, M. (1985) · 1985
Earlier work this paper cites.
Spline Models for Observational Data
Wahba, G. (1990) · 1990
Earlier work this paper cites.
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Wahba, G. and Wang, Y. (1990) · 1990
Earlier work this paper cites.
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Conway, J. (1994) · 1994
Earlier work this paper cites.
Résumé and remarks on the open boundary condition minisymposium
Sani, R. L. and Gresho, P. M. (1994) · 1994
Earlier work this paper cites.
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van der Vaart, A. and Wellner, J. (1996) · 1996
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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