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A new class of kernels for nonparametric curve estimation

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Publication:2366733
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DOI10.1214/aos/1176349021zbMath0777.62041OpenAlexW1982400500MaRDI QIDQ2366733

Karen Messer, Larry Goldstein

Publication date: 19 December 1993

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176349021

zbMATH Keywords

boundary biasGreen's functionconvergence propertiesintegrated mean square errornonparametric curve estimationnew class of variable kernelssmoothing spline estimators


Mathematics Subject Classification ID

Density estimation (62G07) General nonlinear regression (62J02)


Related Items

Nonparametric regression with infinite order flat-top kernels, On the asymptotics of penalized spline smoothing, \(\sqrt{n}\)-consistent parameter estimation for systems of ordinary differential equations: bypassing numerical integration via smoothing, Local and global asymptotic inference in smoothing spline models, Equivalent kernels for smoothing splines, Variance reduction for kernel estimators in clustered/longitudinal data analysis, Joint asymptotics for semi-nonparametric regression models with partially linear structure



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