Are regression series estimators efficient in practice? A computational comparison study

DOI10.1007/S001800000045zbMath1037.62029OpenAlexW3122903510MaRDI QIDQ1424608

Michel Delecroix, Camelia Protopopesku

Publication date: 16 March 2004

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s001800000045

zbMATH Keywords

waveletskernel smoothingcubic splinesorthonormal series estimators

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) General nonlinear regression (62J02) Numerical interpolation (65D05)

Related Items (2)

Estimating the error distribution function in semiparametric additive regression models ⋮ Testing for additivity in partially linear regression with possibly missing responses

Cites Work

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• Smoothing by weighted averaging of rounded points
• Convergence rates for trigonometric and polynomial-trigonometric regression estimators
• Ondelettes sur l'intervalle. (Wavelets on the interval)
• Wavelet regression for random or irregular design.
• Wavelets on the interval and fast wavelet transforms
• Convergence rates and asymptotic normality for series estimators
• Wavelets, approximation, and statistical applications
• Regression series estimators: the mise approach
• Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models
• Orthonormal bases of compactly supported wavelets
• Ten Lectures on Wavelets
• Comparing Automatic Smoothers (A Public Service Enterprise)
• Wavelet Methods for Curve Estimation

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