Non linear wavelet estimation of regression derivatives based on biased data

DOI10.1080/03610926.2018.1473613OpenAlexW2901454306WikidataQ128879462 ScholiaQ128879462MaRDI QIDQ5866063

Huijun Guo, Junke Kou

Publication date: 10 June 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2018.1473613

zbMATH Keywords

waveletsbiased data\(L^p\) riskderivatives function estimation

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40)

Related Items

MISE of wavelet estimators for regression derivatives with biased strong mixing data, Unnamed Item, Adaptive wavelet density estimation under independence hypothesis

Cites Work

• Unnamed Item
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• An extension of Chesneau's theorem
• On multivariate kernel estimation for samples from weighted distributions
• On minimax wavelet estimators
• Density estimation by wavelet thresholding
• Nonparametric Wavelet Regression Based on Biased Data
• Non parametric regression estimations over L^p risk based on biased data
• Wavelet-Based estimation of multivariate regression functions in besov spaces^*
• Linear wavelet estimation of the derivatives of a regression function based on biased data
• On MISE of a Non linear Wavelet Estimator of the Regression Function Based on Biased Data under Strong Mixing
• Wavelet-based estimation of regression function for dependent biased data under a given random design